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TEXAS COMMISSION ON ENVIRONMENTAL QuAlflIn'filVISION Bryan W. Shaw, Ph.D., Chairman Buddy Garcia, Commissioner
Carlos Rubinstein, Commissioner
Mark R. Vickery, P.G., Executive Director

Protecting Texas by Reducing andPreventing Pollution April 1,2010

Docket No. 2009-0801-SIP Project No. 2009-018-SIP-NR**y",·~:·** -,...r;·,

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:::**~-~!'** Alfredo "AI" Armendariz, Ph.D., Regional Administrator U.S. Environmental Protection Agency

- Region 6 1445 Ross Avenue Dallas, Texas 75202-2733 w -**S~2** 

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Dear Dr. Armendariz:

On March 10,2010, the Texas Commission on Environinental Quality (Commission) adopted a revision to the state implementation plan (SIP) for demonstration of reasonable further progress for the Houston-GalvestonBrazoria (HGB) 1997 eight-hour ozone nonattainment area.

The Commission adopted the HGB Reasonable Further Progress (RFP) SIP revision, demonstrating that the RFP emissions reduction requirement will be met for the six-year period (2003-2008) beginning Janumy 1 of the year following the year used for the baseline emissions inventory (2002) and all remaining three-year periods after the first six-year period (2009-2011, 2012-2014, and 2015-2017) out to the area's attainment date (2019). This SIP revision also sets the nitrogen oxides (NOx) and volatile organic compounds (VOC) motor vehicle emissions budgets (MVEB) for transportation conformity purposes for the milestone years 2008, 2011, 2014, 2017, and 2018.

Enclosed are the proposed revision to the SIP, a public hearing certification, a complete record of the public hearings, and the accompanying order. I look forward to your expeditious approval ofthis SIP revision.
Sincerely,

# ~~;dAtv- Bryan W. Shaw, Ph.D. Chairman

BWS/ts

Enclosures

cc: The Honorable Rick Perry, Governor of Texas Mr. Toby Baker, Office of Budget, Planning and Policy, Office of the Governor .Mr. MarkR. Vickery, P.G., Executive Director, Texas Commission on Environmental Quality

P.O. Box 13087 Austin, Texas 78711-3087 512-239-1000 Internet address:www.tceq.state.tx.us

'.' " 'dTexas Commission on Environmental Quality Public Hearings October 28 and 29. 2009
Concerning Revisions to the HGB Eight-Hour Ozone Reasonable Further Progress SIP Project No. 2009-018-SIP-NRREVISION TO THE STATE IMPLEMENTATION PLAN FOR THE CONTROL OF OZONE AIR POLLUTION

HOUSTON-GALVESTON-BRAZORIA 1997 EIGHT-HOUR OZONE STANDARD NONATTAINMENT AREA

TCEQ

TEXAS COMMISSION ON ENVIRONMENTAL QUALITY P.O. BOX 13087 AUSTIN, TEXAS 78711-3087

Houston-Galveston-Brazoria Reasonable Further Progress State Implementation Plan Revision for th e1997 Eight-Hour Ozone Standard

PROJECT NO. 2009-018-SIP-NR

Adopted March 10, 2010HGB Reasonable Further Progress SIP Revisi on for the 1997 Eight-Hour Ozone Standard

ix LIST OF APPENDICES

Appendix Appendix Name

Appendix 1 HGB Reasonable Further Progress Demonstration Calculations Spreadsheet

Appendix 2 Development of Reasonable Further Progress Point Source Inventories

Appendix 3 Development of Reasonable Further Progress Area Source Inventories

Appendix 4 Development of Reasonable Further Progress Non-Road Mobile Source Emissions Inventories for Source Categories in the EPA’s NONROAD 2005 Model

Appendix 5 Development of Reasonable Further Progress Non-Road Mobile Source Emissions Inventories for Airports

Appendix 6 Development of Reasonable Further Progress Non-Road Mobile Source Emissions Inventories for Locomotives

Appendix 7 Development of Reasonable Further Progress Non-Road Mobile Source Emissions Inventories for Commercial Marine Vessels

Appendix 8 Development of Reasonable Further Progress Non-Road Mobile Source Emissions Inventories for Drilling Rigs

Appendix 9 Houston-Galveston-Brazoria 1997 Eight- Hour Ozone Nonattainment Area Reasonable Further Progress On-Road M obile Source Emissions InventoriesAPPENDIX 4

DEVELOPMENT OF REASONABLE FURTHER PROGRESS NON-ROAD MOBILE SOURCE EMISSIONS INVENT ORIES FOR SOURCE CATEGORIES IN THE EPA’S NO NROAD 2005 MODEL

## Technical Support Document

Development of Reasonable Further Progress (RFP) NonRoad Mobile Source Emissions Inventories for Source Categories in the EPA’s NONROAD2005 model



# March 2009

Prepared by the Mobile Source Programs Team Air Quality Division Texas Commission on Environmental Quality

## INTRODUCTION

This technical support document describes th e methodologies used by th e Texas Commission on Environmental Quality (TCEQ) to develop R FP emissions inventory data for all source categories contained within the EPA’s NONROAD 2005 model. The inventories developed include county level ozone season day controlle d and uncontrolled emissions estimates for years 2002, 2008, 2011, 2014, 2017, 2018 and 2019 for th e eight counties in the Houston/Galveston/Brazoria (HGB) ozone non-atta inment areas. The eight counties in HGB area are Brazoria, Chambers, Fort Bend, Galves ton, Harris, Liberty, Montgomery, and Waller.

A Texas specific version of the EPA’s NON ROAD 2005 model, called the Texas NONROAD (TexN) model, was used in calculating emissi ons from all non-road mobile equipments and recreational vehicles except aircrafts, locomotiv es, and commercial marines. TexN was designed to develop emission estimates that are consistent with the latest emission inventory data available for all counties in Texas, for all Source Classi fication Codes (SCCs) incl uded in the NONROAD model. Texas-specific data files included county specifi c equipment population, activity, growth, and temporal alloca tion files as appropriate.

The TexN model also incorporat es extensive data collected to estimate equipment population growth and geographic allocation. Unlike the EPA’s NONROAD 2005 model, the TexN model utilizes unique population files for each county a nd analysis year. Sinc e the population files in TexN for all the years (i.e., 1970-2050) are create d outside the model, for every evaluation year, using county and SCC specific growth factors, the corresponding growth (*.grw) and geographic allocation (*.alo) files used in NONROAD are e ffectively bypassed in the TexN application. Several NONROAD files have not b een revised for SIP development or other purposes, largely due to the difficulty in collecting the required data. The NONROAD default files used in TexN include: Emission factors(*.emf), deterioration factors (*.det ), and engine technology phase-in schedule (tech.dat) files. The EPA does not expect users to have local data on emission factors, or on deterioration factors.

Overview of the TexN model, s ources of data used in TexN a nd calculation procedures were extracted from the TexN user’s guide prepared by Eastern Research Group, Inc. and is attached to this RFP SIP as Attachment A. The deta ils of activity projections for TexN equipment categories with non-default values can be found in Attachment A, Section 1.2.4 Forecasting and Back-Casting Equipment Populations

.
The TexN model includes both emission factors and county-level populati on and activity data. The model therefore estimates not just emission f actors but also emissions. The emission factors are combined with hp-hr and fuel consumption es timates to calculate mass emission estimates at the county level, for different ev aluation years and time periods.

The TexN model used for this RFP analysis is available at the TCEQ’s FTP site at ftp://ftp.tceq.state.tx.us/pub/OEP AA/TAD/Modeling/Nonroad_EI/TexN/ . This FTP site also contains the “Texas NONROAD (TexN) model Version 1.0 User’s Guide”. The Technicaldocumentation of all aspects of the non-road modeling can be found on the EPA’s NONROAD modeling web page at http://www.epa.gov/omswww/nonrdmdl.htm

.

The TexN model includes more than 80 basic a nd 260 specific types of non-road equipment, and further stratifies equipment type s by horsepower rating and fuel t ype, in the following categories:

 airport ground support, such as terminal tractors;

 agricultural equipment, such as tractors, combines, and balers;

 construction equipment, such as graders and back hoes;

 industrial and commercial equipment, such as fork lifts and sweepers;

 recreational vehicles, such as all-terrai n vehicles and off-road motorcycles;

 residential and commercial lawn and gard en equipment, such as leaf and snow blowers;

 logging equipment, such as sh redders and large chain saws;

 recreational marine vessels , such as power boats;

 underground mining equipment; and

 oil field equipment.

The model estimates emissions for seven exhaus t pollutants: hydrocarbons (HC), nitrogen oxides (NO X ), carbon monoxide (CO), carbon dioxide (CO 2 ), sulfur oxides (SO X ), Ammonia, and particulate matter (PM). The model also estima tes emissions of non-exhaust HC for six modes — hot soak, diurnal, refue ling, resting loss, r unning loss, and crankcase emissions.

Although the model is capable of calculating emissions from ground support equipment (GSE), and other oil field equipment, the TCEQ currently estimates GSE, and oil field equipment outside of the NONROAD model and the TexN data base has zero population levels for these categories.



### Federal and State Control Programs Analysis

The effects of federal and stat e control programs were evalua ted. The TexN model was executed for Ozone season daily emission for years 2002, 2008, 2011, 2014, 2017, 2018 and 2019. To evaluate reasonable further progress requirements, a series of TexN mo del runs were executed for both controlled and uncontrolled scenarios for each federal and state control program for each analysis year. The electronic data including emi ssions inventory summary report data files for each of the inventories and the NONROAD input/ output files can be found at the TCEQ’s FTP site at ftp://ftp.tceq.state.tx.us/pub/OEP AA/TAD/Modeling/Nonroad_EI/RFP/HGB

.

The details of the applicable federal and state rules modeled, and how these rules are incorporated in TexN model as reported by TCEQ’s contractor, Eastern Research Group, Inc., in the TexN User’s guide is in Attachment D.

### Federal Controls

The Federal Clean Air Act (FCAA) provides the EPA with the authority to establish emissions standards only for new engines; therefore non-road en gine emissions standards phase in over time as older engines undergo turnover and repl acement. The first of the non-road regulations that the EPA has issued since 1994 to control non-road mobile emi ssion sources went into effect in 1996, and the last went into effect in 2008. The EPA has take n a phased-in approach when adopting these regulations and has issued multiple tiers for certain categories of engines. The TexN model used in this study incorporates th e effects of all of th e following “on the books” Federal non-road equipment regulations:


### Table 1: Existing Federal Non-Road Regulations and Phase - In Dates

Applicable Rules Category Implementation Phase-In

Period

Phase I Small SI Rule Land-Based Spark Ignition Engines < 25hp (except marine and recreational) 1997

Non-Handheld SI Engines < 25hp 2001-2007 Phase II Small SI Rule

Handheld SI < 25hp 2002-2007

Land-Based Diesel Engines >50 hp 1996-2000 1998 HD/Non-road Rule

Or Tier I Rule Small Diesel Engines < 50 hp 1999-2000

Tier 2 Standards Diesel Engines all sizes 2001-2006

Tier 3 Standards Diesel Engines 50-750 hp 2006-2008

Large SI Rule Spark Ignition engines > 25hp Tier 1 - 2004

Tier 2 - 2007

Tier 4 Standards Land-Based Diesel Engines 1996-2000For more details on the applicable rules and ho w the TexN model is designed to evaluate the effects of individual federal rules impacting n on-road emissions for RFP analysis, please see Attachment D. In order to evaluate individual control reductions benefits of each federal rule, a series of TexN model runs were executed for controlled and uncontrolled scenarios. For a summary of control re ductions, see Table 4.



### State Controls

The state rules evaluated for this analysis are discussed below.

 The Texas Low Emission Diesel Rule (TxLED)

 Reformulated Gasoline (RFG)



### Texas Low Emission Diesel

TexLED was implemented on January 31, 2006, for 110 counties in Texas. The TexLED program is incorporated as part of TexN m odel’s post processing function. The TexLED flag was activated for 2006 and later analysis for the 110 counties. Annual modeling scenarios for 2007 and beyond receive a full credit of 6.2% NO X reduction applied to all diesel emissions in TexLED counties.



### Table 2: TexLED NOx Emissi on Reduction Benefits

Typical Summer weekday Emissions (Tons/Day)
8-County HGB Region Analysis Year NO X
2002 0.00

2008 2.87

2011 2.59

2014 2.14

2017 1.73

2018 1.59

2019 1.46

### Reformulated Gasoline

RFG benefits were calculated by running the TexN model for all spark ignition equipment categories and all scenario years, with RVP va lues set to 7.2 (representative of RFG) and 8.7 (federal default RVP for summer fuel in Texa s). The resulting difference in exhaust and evaporative VOC levels is reported in Table 3 for each analysis year.



### Table 3: RFG VOC Emission Reduction benefits

Typical Summer weekday Emissions (Tons/Day)
8-County HGB Region Analysis Year VOC

2002 1.84

2008 1.88

2011 1.97

2014 2.05

2017 2.14

2018 2.16

2019 2.19

### Table 4: State and Federal Contr ol Reduction Summary for NONROAD Mobile Source Categories that are in EPA's NO NROAD2005 Model

NO X VOC Typical Summer Weekday Emissions Typical Summer Weekday Emissions Tons/Day Tons/Day RFP Analysis Year
Uncontrolled Controlled Total Reduction Uncontrolled Controlled Total Reduction 2002 88.63 79.01 9.62 94.86 79.05 17.65
2008 105.38 65.80 39.59 107.12 63.01 45.99 2011 111.17 54.97 56.21 113.37 57.76 57.58 2014 117.09 43.88 73.21 119.27 55.02 66.31 2017 124.33 35.94 82.17 125.34 53.78 72.46 2018 128.11 33.68 94.46 127.18 53.58 75.77 2019 129.41 31.53 97.89 128.88 53.49 77.58

The electronic data including emissions inventory summary report data files for each of the inventories and the NONROAD input/output files can be found at the TCEQ’s FTP site at ftp://ftp.tceq.state.tx.us/pub/OEP AA/TAD/Modeling/Nonroad_EI/RFP/HGB

. Electronic data set names and descriptions for these files are provided in the following section.



### ELECTRONIC DATA SET NAM ES AND DESCRIPTIONS

This section provides the HGB 2002, 2008, 2011, 2014, 2017, 2018, and 2019 RFP non-road mobile source emissions inventor y electronic data descriptions.

The electronic data includes 1) the emissions i nventory summary report data files for each of the inventories and 2) the NONROAD input/output files. These file s are posted at the following TCEQ’s FTP Site: ftp://ftp.tceq.state.tx.us/pub/OEPAA/TAD/Modeling/Nonroad_EI/RFP/HGB

. The files in these compressed folders are based on every TexN runs performed with the October 2008 version of the Texas NONROAD (TexN) model, which contains the most recently updated equipment population estimates.

These compressed data sets contain:

HGB RFP Rule Benefits Anal ysis Excel Spreadsheet files HGB RFP NONROAD input/output filesPlease note that the TexN model accounts for ad justments such as Texas Low Emission Diesel (TxLED), temperature/humidity NOx correction, etc., Therefore, if the EPA’s NONROAD 2005 model is used to replicate the emissions, the re sults may vary slightly because the EPA’s model not does not include these adjustments.

Notes on Non-Road Input/Output Data Sets on the FTP Site

1) The NONROAD INPUT OUTPUT data are in the zip file labele d “input+output". There are folders for each year i.e., 2002 HGB RFP NONROAD 2008 HGB RFP NONROAD 2011 HGB RFP NONROAD 2014 HGB RFP NONROAD 2017 HGB RFP NONROAD 2018 HGB RFP NONROAD and 2019 HGB RFP NONROAD

Within each of the folders, there are 15 folders except for 2002 HGB RFP NONROAD which has 13 folders due to some of the controls not being applicable for 2002 base year.

The folders are for the following scenarios:

20XX Controlled 20XX Controlled - no TexLED 20XX Controlled - no RFG 20XX Large SI Controlled 20XX Large SI Uncontrolled 20XX Small SI Phase I Controlled 20XX Small SI Phase I Uncontrolled 20XX Small SI Phase II Controlled 20XX Small SI Phase II Uncontrolled 20XX Tier I Controlled 20XX Tier I Uncontrolled 20XX Tier 2_3 Controlled 20XX Tier2_3 Uncontrolled 20XX Tier 4 Controlled 20XX Tier 4 Uncontrolled

2). Each of the above mentioned folders, contai n a total of 201 separate folders, the /output/ folder contains the aggregate.out for that particul ar scenario as named in the first level folder. The "Aggregate.out" is a comma-separated values data set that loads very easily into Excel.

3). The TexN model performs 25 separate r uns of the NONROAD model per County coded 01- 25.Generally, the first 25 folders are for the coun ty Brazoria and the second 25 folders are for Chambers and so on in the following order:

- Brazoria - Chambers - Fort Bend - Galveston - Harris - Liberty - Montgomery - Waller

For each county, the TexN model performs separate NONROAD runs for the following 24 diesel construction equipment (DCE) sub-sectors to account for different equipment population and activity profiles within each:

1) Agricultural Activities 2) Boring/Drilling Equipment 3) Brick and Stone Operations 4) City and County Road Construction 5) Commercial Construction 6) Concrete Operations 7) County-Owned Construction Equipment 8) Cranes 9) Heavy-Highway Construction 10) Landfill Operations 11) Landscaping Activities 12) Manufacturing Operations 13) Municipal Owned Construction Equipment 14) Transportation/Sales/Services 15) Residential Construction 16) Rough Terrain Forklifts 17) Scrap/Recycling Operations 18) Skid Steer Loaders 19) Special Trades Contractors 20) Trenchers 21) Texas Department Of Transportation Equipment 22) Utility Construction 23) Mining and Quarry Operations 24) Off-road Tractors, Misc. Equipment, and all Equipment < 25 hp

Run #25 for each County is non-DCE equipment.

Within each of these directories are /inputs/ and /outputs/ subdirectories.

Each /inputs/ directory contains the following NONROAD input files:- input files with an ...opt extension - equipment population files with a ...pop extension - activity files with a ...dat extension

Each /outputs/ directory contains the following NONROAD output files:

- aggregate emissions output with an ...out extension - output message file with an ...msg extension - exhaust emissions by model year with a ...bmx extension - evaporative emissions by model year with a ...bmv extension

1.0 

## References

1. User’s Guide for the Final NONROAD 2005 Model, EPA420-R-05-013, December 2005, http://www.epa.gov/otaq/nonrdmdl.htm 2. NONROAD2005 Emission Factor Model, available from http://www.epa.gov/otaq/nonrdmdl.ht m, last validated 11-18-2006. 3. Texas NONROAD (TexN) Model Version 1.0 User’s Guide, Eastern Research Group prepared for the Texas Commission on Environmental Quality, August 18, 2008. ftp://ftp.tceq.state.tx.us/pub/OEP AA/TAD/Modeling/Nonroad_EI/TexN/

. 4. Eastern Research Group, Ozone Science a nd Air Modeling Research Project H43T163: Diesel Construction Equipment Activity and Emissions Estimates for the Dallas/Ft. Worth Region, prepared for The Houston A dvanced Research Center, August 31, 2005. 5. Eastern Research Group, Statewide Diesel Construction Equipment Inventory, prepared for the Texas Commission on Environmental Quality, August 31, 2005. 6. Eastern Research Group, Nonroad Mobile Source Emissions Invent ory Development for the Houston-Galveston-Brazoria Area, submitted to the Houston-Galveston Area Council, July 28, 2006.Attachment A TexN Overview – Data Sources and Calculation Procedures

Source: Texas NONROAD (TexsN) Model Version 1.0 User’s Guide, Chapter 4 Prepared by: Eastern Research Group, August 18, 20081.0 

## TexN Overview – Data Source s and Calculation Procedures

The TexN model consists of four basic elements:

1) A Graphical User Interface (GUI) 2) A MySQL database 3) EPA’s NONROAD2005 model, and 4) An enhanced Reporting Utility

The TexN GUI was designed to incorporate more user-friendly features than the NONROAD model, accommodating the need for a finer level of emissions processing, and allowing for more detailed docum entation of each run. The inte rface interacts with a MySQL5.0 database, which enhances the user’s ability to manage data, group runs, and document scenarios. The database was populated with all of the equipment population and related activity data developed for the latest State Implementation Pl ans (SIPs) and other periodic inventories for Texas. The database automatically applies post-processing adjustments as appropriate, and creates output files that can be imported into the modified Reporting Utility. The Reporting Utility allows the user enhanced reporting options.

This section provides a detailed overview of TexN data sources, functionality, and processing methodology, focusing on those featur es not included in the standard NONROAD modeling package.

1.1 Accommodation of Constructi on Equipment Subcategories

Diesel construction equipment (DCE) is usually the larg est single emitter of nitrogen oxide (NOx) emissions in urban areas. DCE is also used in a wide variety of different tasks, with different activity and emissions profiles. Acco rdingly, the DCE emissions inventory has been highly disaggregated for Texas, characterizi ng construction equipmen t use for 24 sectors, including highway, commercial bui lding, residential, utility, a nd other distinct construction activities or specialty equipment profiles. Each of the 24 DCE sect ors is listed below.

 Agricultural Activities

 Boring and Drilling Equipment

 Brick and Stone Operations

 City and County Road Construction

 Commercial Construction

 Concrete Operations

 County-Owned Construction Equipment

 Cranes

 Heavy Highway Construction

 Landfill Operations

 Landscaping Activities

 Manufacturing Operations

 Municipal-Owned Construction Equipment Transportation/Sales/Services

 Residential Construction

 Rough Terrain Forklifts

 Scrap/Recycling Operations

 Skid Steer Loaders

 Special Trades Construction

 Trenchers

 TxDOT Construction Equipment

 Utility Construction

 Mining and Quarry Operation

 Off-Road Tractors, Miscellaneous E quipment, and all Equipment under 25 horsepower

The TexN modeling system was designed to ca lculate emissions for each of these sectors individually.

Three factors were considered when defining the DCE categories for Texas. First, the categories are fundamentally different in th eir equipment use requirements (e.g., the tasks required for highway and resident ial projects are quite different ). Second, available population and activity surrogates for each project category should be clear ly associated with actual equipment use to the extent possible. 1 Third, all categories, when c onsidered together, cover the vast majority of DCE use in the State.

In a previous study completed for the Houst on Advanced Research Center titled Ozone Science and Air Modeling Resear ch Project H43T163: Diesel Construction Equipment Activity and Emissions Estimates for the Dallas/Ft. Wo rth Region, experts from various construction sectors and technical representatives from the TC EQ were solicited for their opinions regarding the distinct types of construc tion project categories, the like ly relative contribution of the different categories, and the ava ilability of appropriate surrogat e data for each category. Based on this input it was determined that there ar e two fundamentally di fferent types of DCE categories – those that have significant earthwork and surfacing requirements, and those that do not. Earthwork project categories include:

 Highway construction (state highway a nd bridge work, and city/county roads);

 Utility installation (sewer, water, gas, power, and communication line installation and repair);

 Single Family housing (residential developments/subdivisions); and,

 Commercial structures.

Exhaust emissions are directly related to th e hp-hours of work output by an engine. The hp-hours are in turn associated with the amount of work performed for a given task. While the engine work performed during non-earthwork ta sks may be difficult to quantify (e.g., pothole

1 While it is not possible to directly estimate hours of equipment use for all DCE categories, certain correlates of activity have been identified and collected for the different project categories, such as the linear feet of utility line installation per year.patching, or the amount of lifting performed by cranes), earthwork and surfacing tasks are reasonably straightforward to quantify and link to available physical quantity surrogates. Therefore, by developing equipment activity profile s directly in terms of physical quantities such as cubic yards of earth moved, it became possibl e to develop more precise correlates for equipment activity for the earthwo rk categories listed above.

Non-earthwork project categories may also involve the use of DCE. Equipment use for these categories may involve specialized activi ties (e.g., landfill compacting). In other cases the work performed may involve earthmoving and/or surfacing, but cannot be determined from available surrogates (e.g. for mini ng activities, where production data is considered confidential business information).

The following lists the non-earthwork DCE categories used in Texas:

 Road or utility maintenance/repair activities performed by municipalities/counties/state agencies;

 Landfill operations;

 Surface mining – including stone/quarry operations, sand/aggregate pits; and,

 Boring/drilling operations, including water wells, deep foundation work (piles/piers), and utility pole installation/repair.

A database of DCE purchases in the Dalla s- Fort Worth area was obtained to help identify other industry sectors that are also significant users of DCE. These include:

 Special construction trades (e.g., performing post-earthwork activities such as concrete, electrical, heating and air c onditioning installation, and other tasks);

 Landscaping companies;

 Agricultural entities;

 Scrap handling and recycling facilities;

 Concrete product manufacturers;

 Brick and stone produc t manufacturers;

 General manufacturing operations; and,

 Transportation/Wholesale a nd Retail Sales/Services.

Other DCE categories were also found to be inadequately characte rized by the earthwork profiles. These equipment types are numerous a nd therefore potentially significant emitters, but were often difficult to link to available earthwo rk or surfacing surrogates. These included:

 Cranes;

 Rough terrain forklifts;

 Skid steer loaders; and,

 Trenchers.

Population data for these equipment types were derived from an equipment sales database, with activity estimates provided by industry experts, fo r both earthwork and nonearthwork project categories.Table 1-1 summarizes the equipment types found within each of the 24 DCE sub sectors.Table 1-1. DCE Type by Sub sectorEquipment DescriptionSCC 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24Pavers2270002003 x x x x x x x x x x x xTampers/Rammers 2270002006 xPlate Compactors 2270002009 xRollers2270002015 x x x x x x x x x x x x x xScrapers2270002018 x x x x x x x x x x x x x xPaving Equipment 2270002021 x x x x x xSurfacing Equipment 2270002024 x x x x x x x xSignal Boards/Light Plants 2270002027 xTrenchers2270002030 x xBore/Drill Rigs2270002033 x xExcavators2270002036 x x x x x x x x x x x x x x x x x x xConcrete/Industrial Saws 2270002039 xCement & Mortar Mixers 2270002042 xCranes2270002045 x xGraders2270002048 x x x x x x x x x x x x x x x xOff-highway Trucks 2270002051 x x x x x x x x x x xCrushing/Proc. Equipment 2270002054 x xRough Terrain Forklifts 2270002057 x xRubber Tire Loaders 2270002060 x x x x x x x x x x x x x x x x x x xTractors/Loaders/Backhoes 2270002066 x x x x x x x x x x x x x x x x x x xCrawler Tractor/Dozers 2270002069 x x x x x x x x x x x x x x x x x xSkid Steer Loaders 2270002072 x xOff-Highway Tractors 2270002075 x xDumpers/Tenders 2270002078 xOther Construction Equipment 2270002081 xSub sector Key:25)Agricultural Activities26)Boring/Drilling Equipment27)Brick and Stone Operations28)City and County Road Construction29)Commercial Construction30)Concrete Operations31)County-Owned Construction Equipment32)Cranes33)Heavy-Highway Construction34)Landfill Operations35)Landscaping Activities36)Manufacturing Operations37)Municipal Owned Construction Equipment38)Transportation/Sales/Services39)Residential Construction40)Rough Terrain Forklifts41)Scrap/Recycling Operations42)Skid Steer Loaders43)Special Trades Contractors44)Trenchers45)TxDOT Equipment46)Utility Construction47)Mining and Quarry Operations48)Off-road Tractors, Misc. Equipment, and all Equipment < 25 hp1.2 Development of Texas-Specific Data Files

TexN was designed to develop emission es timates (including ammonia) that are consistent with the latest em issi on inventory data available for all counties in Texas, for all SCCs included in the NONROAD model. The resulting emission factors are combined with hp-hr and fuel consumption estimates to calculate mass emissi on estimates at the count y level, for different evaluation years and time periods.

In order to develop the required Texas-specif ic data files, ERG developed, compiled, and organized the NONROAD model file s needed to generate the mo st up-to-date county level nonroad mobile emissions inventories for the state. These data included area specific equipment population, activity, growth, and temporal allocation files as appropriate. Base years for these data included 1999, 2000, 2002, and 2004.

ERG then developed and populated baseline and projected inve ntory lookup tables, reflecting variations in fuel properties, temperature, and selected control strategies, at the county and SCC level. These tables can be easily modifi ed using the TexN GUI to perform sensitivity or other analyses. Look-up tables fo r county-specific diesel activity adjustment factors were also compiled for altitude, ground cover, and soil propert ies. Note these adjustment factors are not input directly into the model, but are applied as linear corrections duri ng the post-processing of output files. (Details regarding these and other post-pro cessing adjustments are provided in Section 1.3.)

Using the files described above, TexN can produce emissions estimates of VOC, NOx, SO 2 , CO, PM 10 , and PM 2.5 for any county and time period of interest. For ammonia estimates, selected ammonia emission fact ors are applied to the adjust ed NONROAD output files for each county and SCC and for each base year. The NONR OAD output files are then post-processed to aggregate by model year and technology groups a nd fuel types. Emission factors are then combined with the NONROAD output data, using th e appropriate aggregated hp-hr and/or fuel consumption estimates to obtain mass emissions estimates for ammonia.

The most recent available data was identified and collected in order to populate the following NONROAD model files, for each county and SCC combination, for the possible range of analysis years (1970 – 2050). File naming co nventions are provided in parentheses.

 Option file (*.opt - temperature and fuel specification data)

 Equipment Population by hp bin (*.p op – equipment counts by hp bin)

 Activity (activity.dat - hr/yr)

 Temporal allocation (season.dat - weekday/weekend, and seasonal)

In addition, extensive data were also collect ed to estimate equipment population growth and geographic allocation. However, due to the calculation methodology employed within TexN which utilizes unique population files for each county and analysis year, the correspondinggrowth (*.grw) and geographic allocation (*.a lo) files used in NONROAD are effectively bypassed in the TexN application. 2

Several NONROAD files have not been revised for SIP development or other purposes, largely due to the difficulty in collecting th e required data. In these cases NONROAD default files were used for emissions estimation. These default files include:

 Emission factors (*.emf)

 Deterioration factors (*.det files)

 Engine technology phase-i n schedule (tech.dat)

The following summarizes the sources of the data collected in order to generate the above NONROAD files.

1.2.1 TexN Fuel Specification Data

The NONROAD2005 model requires inputs for the following fields, in order to generate the primary input file (known as the OPT or Options file).

 Gasoline Reid Vapor Pressure (RVP)

 Gasoline oxygen weight percent

 Gasoline sulfur weight percent

 Diesel sulfur weight percent

 Recreational marine diesel sulfur weight percent

 CNG/LPG sulfur weight percent

No Texas-specific data was identified for re creational marine diesel and CNG/LPG sulfur levels, so NONROAD default values were retained; 0.2637% and 0.003% , respectively. [2]

General summer fuel specifications for Texas are summarized in Table 1-2 below, developed for the TCEQ for on-road modeling.

Table 1-2. Federal and State Fuels Contro ls in Texas During Summer Season Period 3

Program Start Year Control/Standard Geographic Coverage Federal Controls on Gasoline Volatility 1 1992 Max RVP, 7.8 pounds per square inch (psi) Max RVP, 9.0 psi One-hour ozone nonattainment counties 2 Remainder of state

2 Unlike NONROAD which utilizes one state-level population file, which is in turn allocated to the county level using the *.alo files, TexN contains unique population files for all 254 counties in the state. Therefore the additional allocation step employed by NONROAD is not required with in TexN. In addition, separate population files have been developed for every possible Episode Year, utilizing co unty and SCC-specific growth factors, as discussed in Section 4.2.3. While NONROAD’s default growth file is retained within TexN to establish model year distributions, it is not used to forecast or b ack-cast actual equipment populations.
3 Texas Transportation Institute, Development of On-Road, Mobile Source, 1999 Through 2035 Emissions Trends for all 254 Counties, prepared for the TCEQ, August 2004.Federal Reformulated Gasoline (RFG 3 ) 1995 Performance standard reductions: VOC, NOx, Toxics One-hour ozone nonattainment counties for HGA, DFW

El Paso LowRVP Gasoline 4 1996 Max RVP, 7.0 psi El Paso CountyRegional LowRVP Gasoline 5 2000 Max RVP, 7.8 psi 95 central and eastern Texas counties 6

Tier 2 LowSulfur Gasoline 2005 Refinery average 30 parts per million (ppm) gasoline sulfur
content National

Federal LowSulfur Highway Diesel 7, 8 1993/2006 500 ppm maximum sulfur
content 15 ppm maximum sulfur
content National

Texas LowEmission Diesel 9 2005/2006 500 ppm maximum sulfur 15 ppm maximum sulfur

Low aromatic HC and high cetane number to control NOx 110 counties: 95 central and eastern Texas counties 6 and the 15 HGA, BPA, and DFW one-hour ozone nonattainment counties

1. 40 CFR § 80.27. Controls and Prohibitions on Gasoline Volatility. 2. The 16 Texas one-hour ozone nonattainment areas and resp ective counties are: Beaumont/Port Arthur (BPA): Hardin, Jefferson, Orange; Dallas/Fort Worth (DFW): Collin, Denton, Da llas, Tarrant; Houston/Ga lveston (HGA): Brazoria, Chambers, Fort Bend, Galvesto n, Harris, Liberty, Montgomery, Waller; and El Paso County. 3. 40 CFR § 80.41 Standards and Requi rements for Compliance (federal RFG). 4. 30 TAC §§ 115.252. Control Requirements (for gasoline RVP). 5. 30 TAC § 114.301. Control Requi rements For Reid Vapor Pressure. 6. Anderson, Angelina, Aransas, Atascosa , Austin, Bastrop, Bee, Bell, Bexar, Bo sque, Bowie, Brazos, Burleson, Caldwell, Calhoun, Camp, Cass, Cherokee, Colorado, Co mal, Cooke, Coryell, De Witt, Delta, Ellis, Falls, Fannin, Fayette, Franklin, Freestone, Goliad, Gonzales, Grayson, Gr egg, Grimes, Guadalupe, Harrison, Hays, Henderson, Hill, Hood, Hopkins, Houston, Hunt, Jackson, Jasper, Johnson, Karnes , Kaufman, Lamar, Lavaca, Lee, Leon, Limestone, Live Oak, Madison, Marion, Matagorda, McLennan, Mi lam, Morris, Nacogdoche s, Navarro, Newton, Nueces, Panola, Parker, Polk, Rains, Red River, Refugio, Robertson, Rockwall, Rusk, Sa bine, San Jacinto, San Patricio, San Augu stine, Shelby, Smith, Somervell, Titus, Travis, Trinity, Tyler, Upshur, Van Zandt, Victoria, Walk er, Washington, Wharton, Willia mson, Wilson, Wi se, and Wood. 7. 1993 sulfur limit source: “Regulatory Imp act Analysis: Heavy-Duty Engine and Vehi cle Standards and Highway Diesel Fuel Sulfur Control Requirements.” EPA, December 2000 (EPA420-R-00-026). 8. 2006 sulfur limit sour ce: heavy-duty 2007 rule. 9. 30 TAC § 114.312. Low Emi ssion Diesel (LED) Standards.
More detailed, site-specific fuel specifications were also sought by s eason and year at the county level for inclusion within TexN. Histor ical gasoline and diesel fuel sampling data collected for the TCEQ was used to populate the n eeded specification table. Gasoline data were collected in different regions across the state for summertime fuel in 2001, 2003, 2004, and 2005 [3, 4, 5, and 6]. Diesel samples were co llected in 2003, 2004, and 2005 [3, 4, and 5]. In addition, one set of wintertime gasoline sampling was performed in 2006 [6]. In each of the studies fuel samples were collected at randomly se lected retail stations in each of the 25 Texas Department of Transportation (Tx DOT) regions of the state. In order to obtain county level specificity, each county in the state was assign ed to one of the 25 TxDOT regions. This data provided gasoline RVP, oxygen weight percent, and gasoline as well as di esel sulfur weight percent for all locations.

In consultation with the TCEQ, alternative da ta and assumptions were employed in order to gap fill gasoline and diesel fuel specificat ions for years in which there was no samplingperformed. The following summarizes the decisi on rules developed to estimate gasoline and diesel fuel specifications fo r years without sampling data.

5) 2002 summer gasoline parameters are set equal to measured 2001 values; 6) Summer gasoline RVP values for 20 06 and beyond are set equal to 6.8 for counties using reformulated gasoline (RFG) and El Paso, 7.8 for counties subject to the East Texas RVP limitation, and 8.7 for all other counties; 7) 2000 summertime gasoline RVP levels are set equal to valu es from the TRW Petroleum Technologies Survey (formerl y the National Institute for Petroleum and Energy Research), obtained from the TCEQ; 8) 1999 and earlier gasoline RVP levels fo r non-RFG counties are set equal to 9.0, representing levels prior to the East Texas RVP limitation; 9) Summertime gasoline sulfur levels for y ears without sampling data are set equal to the values in EPA’s on-road emissi on factor model MOBILE6.2, as shown in Table 1-3.

Table 1-3. Gasoline Average Sulfur Levels (% weight) [15]

Year RFG Conventional Gas 1999 and earlier* 0.0300 0.0300 2000* 0.0150 0.0300

2001 0.0149 0.0299 2002* 0.0129 0.0279

2003 0.0120 0.0259 2004 0.0120 0.0121 2005 0.0090 0.0092 2006* 0.0030 0.0033 2007** 0.0030 0.0033 2008+** 0.0030 0.0030 * Years without sampling data ** Data available but not yet incorporated into TexN

10) Gasoline oxygenate levels for years wit hout sampling data are set equal to 2.1% by weight for summertime RFG areas, 3.5% for wintertime RFG areas, and to 0% for other areas. 11) If the sampled oxygenate content for gasolin e is greater than 5.0%, then the value was set equal to 5.0%. 4 12) For wintertime gasoline, sampled data for 2006 were used for RVP, sulfur and oxygenate content. For other years MOBI LE6.2 defaults were used for sulfur content (see Table 1-2), and RVP data from TRW wintertime surveys, obtained from the TCEQ; 13) For diesel fuel other than that used by recreational marine engines, the sampled data for 2003, 2004, and 2005 were used. (Not e that diesel fuel specifications do not vary seasonally as do gasoline speci fications, so parameter values are not differentiated by season.)

4 NONROAD2005 does not accept oxygenate inputs greater th an 5.0% by weight [2].14) Diesel sulfur levels prior to 2003 were se t equal to measured 2003 values. Values for 2006 – 2009 were set equal to 2005 values, to account for the introduction of the federal non-road diesel fuel standards in 2007. 5 15) Diesel sulfur levels beyond 2009 were set equal to the average value of 0.0015% by weight under the EPA Clean Air N onroad Diesel – Tier 4 Final Rule.

The final county level fuel specifications are summarized for each season and calendar year, for both gasoline and diesel fuel, in Attachment B. These data were used to generate NONROAD OPT files specific to each county, season, and analysis year.

1.2.2 TexN Climate Data

NONROAD utilizes daily high, lo w and average temperature da ta, primarily to calculate evaporative emissions fro m gasoline engines. These data are required as part of NONROAD’s OPT file. In addition, related da ta on relative humidity and atmo spheric pressure are also used during TexN’s post-processing of NONROAD model outputs to adju st diesel NOx emissions for temperature and humidity effects. Ideally, these data should be specific to each county and episode day of interest. Although meteorological data were not av ailable at this level for all counties, daily temperature, relative humidi ty, and atmospheric pressure information was available for 17 weather stations across the state, from the Texas A&M Energy Systems Laboratory [7]. The 17 weather stations with av ailable data are presented in Table 1-4.

Table 1-4. Weather Stations Pr oviding Daily Climate Data [7]

No. Weather Station City County Location

1 ABI Abilene Taylor Abilene Regional Airport 2 AMA Amarillo Potter Amarillo International Airport 3 ATT Austin Travis Austin Camp Mabry 4 BRO Brownsville Cameron Brownsv ille S. Padre Island International 5 CRP Corpus Christi Nueces Corpus Christi International Airport 6 ELP El Paso El Paso El Paso International Airport 7 DFW Fort Worth Tarrant Dallas - Fort Worth International Airport 8 IAH Houston Harris Houston Bush Intercontinental 9 LBB Lubbock Lubbock Lubbock International Airport 10 GGG Lufkin Angelina Longview E. Texas Regional Airport 11 MAF Midland Midland Midl and International Airport 12 BPT Port Arthur Jefferson Port Arthur S.E. Texas Regional Airport 13 SJT San Angelo Tom Green San Angelo Mathis Field 14 SAT San Antonio Bexar San An tonio International Airport 15 VCT Victoria Victoria Victoria Regional Airport 16 ACT Waco McLennan Waco Regional Airport 17 SPS Wichita Falls Wichita Wichita Falls Municipal Airport

5 The 2005 diesel sulfur values were all lower than the 500 ppm cap set by the federal non-road requirements for Large Refiners and Importers for the 2007 – 2009 period. For this reason 2005 sulfur levels were assumed to hold constant until the 2010 non-road requirements commence (15 ppm).Hourly temperature and relative humidity da ta were obtained for ea ch of these weather stations for 1999, 2000, and 2002, as well as an averaged “typ ical meteorological year” developed by the Energy Systems Laboratory. Th is data has been provided to the TCEQ in electronic format. From the hourly data ERG extracted the daily minimum, maximum, and average temperatures, and average relative humidit y. These values were then sorted into four seasonal groups: winter (December – February), spring (March – May), summer (June – August), and fall (September – November). Fo r each of these seasonal groupings, and for each of the four years, averages were calculate d for daily minimum, maximum, and average temperatures, as well as averages for relative hu midity. These values are used as inputs by TexN for NONROAD modeling as well as post-processing adjustments for NOx, and are provided in Attachment B.

1.2.3 Population, Activity, and Allocation Data

The NONROAD model utilizes equipment populati on and activity data specific to each region of the country, allowing the user to characterize equipmen t em issions at the county level for past and future years, at different temporal scales (i.e., daily, seasonal, and annual emissions). The default values developed by the EPA are based on national level population and activity data. The model allocates equipment counts a nd activity to the county level using readily available surrogates, such as census population fo r lawn and garden equipment, and dollar value of construction projects for construction equipment.

The TCEQ and others have conducted severa l studies over the ye ars to collect region specific population and activity data for selected non-road engine categories, in order to improve upon NONROAD default estimates. Working with TCEQ staff, ERG compiled a comprehensive list of the most recent data developed for differe nt equipment types and regions of the State for inclusion in the TexN model. The sources of the data for each equipment type and region are presented in Tables 1-5 thr ough 1-10 below. The methods used to estimate equipment populations and activity levels ca n be quite complex; in depth discussions of the various methodologies used are provided in the referenced studies.Table 1-5. Sources of Equipment Population DataEquipment TypesRegionData SourceDiesel Construction Equipment > 25 hpDallas-Fort Worth (DFW) 9-countynonattainment area6Eastern Research Group, Ozone Science and AirModeling Research Project H43T163: DieselConstruction Equipment Activity and EmissionsEstimates for the Dallas/Ft. Worth Region, preparedfor The Houston Advanced Research Center, August31, 2005 [8]Diesel Construction Equipment > 25 hp,except HGB7cranesStatewide excluding 9-county DFW area Eastern Research Group, Nonroad AmmoniaEmissions Inventory Development, prepared for TexasCommission on Environmental Quality, November 24,2006 [14]Diesel CranesHouston-Galveston-Brazoria (HGB)nonattainment areaEastern Research Group, Nonroad Mobile SourceEmissions Inventory Development for the HoustonGalveston-Brazoria Area, submitted to the HoustonGalveston Area Council, July 28, 2006 [10]LPG ForkliftsDFW 9-county area and HGBnonattainment areasEastern Research Group, Data Collection, Samplingand Emissions Inventory Preparation Plan for SelectedCommercial and Industrial Equipment: Phase II, FinalReport, prepared for the Texas Commission onEnvironmental Quality, August 31, 2005 [11]Terminal Tractors and TransportationRefrigeration UnitsDFW 9-county nonattainment area Eastern Research Group, Data Collection, Samplingand Emissions Inventory Preparation Plan for SelectedCommercial and Industrial Equipment: Phase II, FinalReport, prepared for the Texas Commission onEnvironmental Quality, August 31, 2005 [11]Transportation Refrigeration Units HGB nonattainment areaEastern Research Group, Nonroad Mobile SourceEmissions Inventory Development for the HoustonGalveston-Brazoria Area, submitted to the HoustonGalveston Area Council, July 28, 2006 [10]6Includes Collin, Dallas, Denton, Ellis, Johnson, Kaufman, Parker, Rockwall, and Tarrant Counties.7Includes Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Montgomery, and Waller Counties.Equipment TypesRegionData SourceCommercial Lawn and GardenStatewideEastern Research Group, Development of CommercialLawn and Garden Emissions Estimates for the State ofTexas and Selected Metropolitan Areas, prepared forTexas Commission on Environmental Quality,November 24, 2003 [12]Recreational MarineStatewideEastern Research Group, Recreational MarineEmissions Inventory, prepared for the TexasCommission on Environmental Quality, August 28,2002 [13]All remaining equipment –see below See belowNONROAD defaults - User’s Guide for the FinalNONROAD2005 Model, EPA420-R-05-013,December 2005 [1]Equipment population estimates were taken from NONROAD defaults for the following equipment categories.

 Agricultural – all equipment/fuel types

 Commercial – all equipment/fuel types

 Logging – all equipment/fuel types

 Railroad – all equipment/fuel types

 Recreational vehicles – all equipment/fuel types

 Residential lawn and garden – all equipment/fuel types

 Industrial – all equipment/fuel types ex cluding LPG forklifts in DFW and HGB, Transportation Refrigeration Units and Terminal Tractors in DFW

 Construction and Mining – all gasoline, LPG, CNG

 Construction and Mini ng – diesel < 25 hp

 Construction and Mini ng – diesel > 25 hp: Tampers/Rammers Plate Compactors Signal Boards/Light Plants Concrete/Industrial Saws Crushing/Processing Equipment Cement/Mortar Mixers Dumpers/Tenders Off-Highway Tractors Other Construction Equipment

Table 1-6. Spatial Allocation Surrogates for Diesel Construction Equipment

Sector Surrogate Agricultural Dollar value outputs from Texas Regional Economic Models, Inc. ( REMI) model* Boring and Drilling Equipment EDA data and dollar value outputs from TX REMI model* Brick and Stone Operations Dollar va lue outputs from TX REMI model* City and County Road Construction Project Dollar Value from Reed Construction Data Commercial Construction Building f ootprint data from McGraw Hill Corporation (MHC) Concrete Operations Dollar valu e outputs from TX REMI model* County-Owned Construction Equipment County level census projections Cranes EDA data and dollar value outputs from TX REMI model* Heavy Highway Construction Project la ne-mile data by county from TxDOT Landfill Operations Landfill disposal volumes from TCEQ Landscaping Activities Dollar value outputs from TX REMI model* Manufacturing Operations Dollar valu e outputs from TX REMI model* Municipal-Owned Construction Equipment County level census projections Transportation Sales/Services Dollar va lue outputs from TX REMI model*Sector Surrogate Residential Construction Historical housing permit records and population growth rates from county-level census projections Rough Terrain Forklifts EDA data and dollar value outputs from TX REMI model* Scrap/Recycling Operations Dollar va lue outputs from TX REMI model* Skid Steer Loaders EDA data and dollar value outputs from TX REMI model* Special Trades Construction Dollar va lue outputs from TX REMI model* Trenchers EDA data and dollar value outputs from TX REMI model* TxDOT Construction Equipment None – TxDOT provided complete county-level population data Utility Construction Project Dollar value from Reed Construction Data and MHC * State level extrapolation and county alloca tion using 9-county DFW population as basis.Table 1-7. Sources of Geographic Allocation Data (Non-DCE)Equipment TypesRegionData SourceLPG Forklifts9-county DFW area and HGBnonattainment areasEastern Research Group, Data Collection, Sampling and EmissionsInventory Preparation Plan for Selected Commercial and IndustrialEquipment: Phase II, Final Report, prepared for the Texas Commission onEnvironmental Quality, August 31, 2005 [11]Terminal Tractors andTransportationRefrigeration Units9-county DFW nonattainment area Eastern ResearchGroup, Data Collection, Sampling and EmissionsInventory Preparation Plan for Selected Commercial and IndustrialEquipment: Phase II, Final Report, prepared for the Texas Commission onEnvironmental Quality, August 31, 2005 [11]TransportationRefrigeration UnitsHGB nonattainment area Eastern Research Group,Nonroad Mobile Source Emissions InventoryDevelopment for the Houston-Galveston-Brazoria Area, submitted to theHouston-Galveston Area Council, July 28, 2006 [10]Commercial Lawn andGardenStatewide Eastern Research Group, Development of Commercial Lawn and GardenEmissions Estimates for the State of Texas and Selected MetropolitanAreas, prepared for Texas Commission on Environmental Quality,November 24, 2003 [12]Recreational Marine StatewideEastern ResearchGroup, Recreational MarineEmissions Inventory,prepared for the Texas Commission on Environmental Quality, August 28,2002 [13]All remaining equipment– see belowSee below NONROAD defaults - User’sGuide for the Final NONROAD2005Model, EPA420-R-05-013, December 2005 [1]Geographic allocation surrogates weretaken from NONROAD defaults for the following equipment categories.Agricultural – all equipmentCommercial – all equipmentLogging – all equipmentRailroad – all equipmentRecreational vehicles – all equipmentResidential lawn and garden – all equipmentIndustrial – all equipment/fuel types excluding LPG forkliftsin DFW and HGB, TRUs and Terminal Tractors in DFWTable 1-8. Sources of Equipment Activity DataEquipment TypesRegionData SourceDiesel CranesHGB nonattainment areaEastern Research Group, Nonroad MobileSource Emissions Inventory Development forthe Houston-Galveston-Brazoria Area,submitted to the Houston-Galveston AreaCouncil, July 28, 2006 [10]Diesel Construction Equipment > 25 hp9-county DFW nonattainment area Eastern Research Group, Ozone Science andAir Modeling Research Project H43T163:Diesel Construction Equipment Activity andEmissions Estimates for the Dallas/Ft. WorthRegion, prepared for The Houston AdvancedResearch Center, August 31, 2005 [8]Diesel Construction Equipment > 25 hp Remainder of State,except HGB cranes Eastern Research Group, Nonroad AmmoniaEmissions Inventory Development, preparedfor Texas Commission on EnvironmentalQuality, November 24, 2006 [14]LPG Forklifts9-county DFW and HGB nonattainment areas Eastern Research Group, Data Collection,Sampling and Emissions Inventory PreparationPlan for Selected Commercial and IndustrialEquipment: Phase II, Final Report, preparedfor the Texas Commission on EnvironmentalQuality, August 31, 2005 [11]Terminal Tractors and TransportationRefrigeration Units9-county DFW nonattainment area Eastern Research Group, Data Collection,Sampling and Emissions Inventory PreparationPlan for Selected Commercial and IndustrialEquipment: Phase II, Final Report, preparedfor the Texas Commission on EnvironmentalQuality, August 31, 2005 [11]Transportation Refrigeration UnitsHGB nonattainment area Eastern Research Group, Nonroad MobileSource Emissions Inventory Development forthe Houston-Galveston-Brazoria Area,submitted to the Houston-Galveston AreaCouncil, July 28, 2006 [10]Equipment TypesRegionData SourceCommercial Lawn and GardenStatewideEastern Research Group, Development ofCommercial Lawn and Garden EmissionsEstimates for the State of Texas and SelectedMetropolitan Areas, prepared for TexasCommission on Environmental Quality,November 24, 2003 [12]All remaining equipment – see equipmentpopulation list aboveSee equipment population list above NONROAD defaults - User’s Guide for theFinal NONROAD2005 Model, EPA420-R-05-013, December 2005 [1]Table 1-9. Activity Surrogates for Construction Equipment

Sector Estimation Method Agricultural Industry expert profiles Boring and Drilling Equipment Industry expert profiles Brick and Stone Operations Industry expert profiles City and County Road Construction Reed Construction profile Commercial Construction Square feet of installed building space from MHC Concrete Operations Industry expert profiles County-Owned Construction Equipment Survey findings from HARC study Cranes Industry expert profiles Heavy Highway Construction Survey findings from H-GAC study Landfill Operations Survey profile from TCEQ study Landscaping Activities Industry expert profiles Manufacturing Operations Industry expert profiles Municipal-Owned Construction Equipment Survey findings from HARC study Transportation Sales/Services Industry expert profiles Residential Construction Single fa mily housing construction profile Rough Terrain Forklifts Industry expert profiles Scrap/Recycling Operations Industry expert profiles Skid Steer Loaders Industry expert profiles Special Trades Construction Industry expert profiles Trenchers Industry expert profiles TxDOT Construction Equipment Engine clock hours provided by TxDOT Utility Construction Linear feet inst alled from Reed Construction DataTable 1-10. Sources of Temporal Allocation FactorsEquipment TypesRegionData SourceDiesel Construction Equipment > 25 hp9-county DFW nonattainment area Eastern Research Group, Ozone Science andAir Modeling Research Project H43T163:Diesel Construction Equipment Activity andEmissions Estimates for the Dallas/Ft. WorthRegion, prepared for The Houston AdvancedResearch Center, August 31, 2005 [8]Diesel Construction Equipment > 25 hp Statewide excluding 9-county DFW area Eastern Research Group, Nonroad AmmoniaEmissions Inventory Development, preparedfor Texas Commission on EnvironmentalQuality, November 24, 2006 [14]LPG Forklifts9-county DFW and HGB nonattainment areas Eastern Research Group, Data Collection,Sampling and Emissions Inventory PreparationPlan for Selected Commercial and IndustrialEquipment: Phase II, Final Report, preparedfor the Texas Commission on EnvironmentalQuality, August 31, 2005 [11]All remaining equipment – see equipmentpopulation list aboveSee equipment population list above NONROAD defaults - User’s Guide for theFinal NONROAD2005 Model, EPA420-R-05-013, December 2005 [1]Once identified, data was obtained for inclusio n in the TexN data files. In all but one instance, the required data was available in el ectronic format at ERG. For the remaining instance, ERG contacted TCEQ staff to obtain revi sed county level allocati on factors for oil field equipment. See an explanation from TCEQ about the oil field equipmen t allocation methodology in Attachment C. 8 Default statewide oil field equipm ent population estima tes from NONROAD were subsequently allocated to the county le vel using these factors (see Attachment D).

Development of Population Files by Analysis Year

Upon review of the above data sets, the co mmercial, utility, and heavy-highway sectors for diesel construction equipment were found to have highly variab le population su rrogate values from one year to the next. The variability wa s most pronounced for certain rural counties where the amount of project work can change dramatic ally from year to year. Accordingly, the surrogates used as growth indi cators for these sectors (dollar value of construction forcommercial, linear feet of installation for utility, and lane-miles of construction for heavyhighway), can also vary drama tically from one year to the next in these locations.

In these instances equipment activity does not increase or decrease relatively smoothly from year to year, as assumed by the NONROAD model, reflecting regional economic patterns. In actuality, contractors increase the equipmen t population as needed to complete projects, subsequently removing them upon project comple tion. In counties containing large metropolitan areas, project-specific fluctuations are usually not noticeable, and changes in overall equipment population will likely follow economic factors fo r the most part, as assumed by NONROAD. However, in some rural counties project-specific fluctuations can be the dominant factor in determining overall activity levels. In these case s the yearly change in activity does not follow a smooth, relatively small annual increase or decrea se, but more closely resembles a step function up or down. Such step functions create discontin uities in the NONROAD growth algorithm, and can result in anomalously large equipment population estimates fo r these construction sectors.

For example, the data on lane-miles of construc tion clearly indicate that a relatively large highway project was performed in Blanco County in 2002-2003. If this data were used without adjustment in the NONROAD growth files, the model would assume a several-fold increase in the county’s highway equipment population begi nning in 2002. More importantly, the model would assume that this equipment remained operati ng in the county in subsequent years, even as growth factors drop back down dramatically in 2004 and beyond. This is because the growth factors only impact the assumed incremental equipm ent purchases in the county for that year. In order to properly account for a drastic reduction in equipment population after completion of a large project in these counties, the NONROAD mode l’s scrap curve would have to be altered for each county and year, for each construction sector.

Therefore, in order to correct for these “project-induced” discontinuities, separate population files were develope d for every possible Analysis Year, for each county and equipment category. To this end growth factors (d escribed in Section 1.2.4) were applied to the base year equipment population files, forecas ting population totals fo r each SCC through 2050,

8 Email from Greg Lauderdale, TCEQ, November 13, 2007and back-casting estimates to 1970. In this way TexN bypasses NONROAD’s growth algorithm, effectively running base year equipment profile s for every scenario. (The default NONROAD growth file, nation.grw, is reta ined within TexN though, and is used to develop model year distributions for any given analysis year.)

1.2.4 Forecasting and Back-Casting Equipment Populations

A variety of growth indicator s or surrogates ma y be used to forecast and back-cast nonroad equipment population and activity estimates, depending upon the equipment type. The Emissions Inventory Improvement Program (EIIP ) recommends several options, as shown in Table 4-11.Table 1-11. EIIP Non-road Growth Indicator Recommendations 9

The previous version of the TexN model projected emissions from 1999 through 2013, utilizing the most appropriate available surrog ates for each DCE sub sector. This section documents the efforts ERG made to update the TexN model to accommodate emissions projections for the entire NONROAD model reporting period, from 1970-2050. Activity projections for TexN equipment categories w ith non-default values were developed from existing data, consistent with current projec tion methodologies to the extent possible.

The TexN model contains 24 distinct “secto rs” with distinct equipment population and activity profiles. 23 of these sectors involv e diesel construction equipment (DCE) profiles developed specifically for TCEQ and the TexN model. A summary of the growth factor surrogates selected for each sector is presented in the table below.

9 GSP = Gross State Product; LTO = Landing/Take-Off cycle.Equipment Sector Grow th Factor Surrogates

Non-DCE Default NONROAD005 Agricultural DCE Texas Agricultural Census for land in farms, forecast and back-cast using total county acreage as a constraint to projections Commercial Construction Economy.com output projections for non-residential construction sectors Heavy-Highway TxDOT Annual Expenditures (1998 - 2006), forecast and back-cast using Economy.Com projections for highway construction sector Residential 1970 - 1979 based on state-level growth rates from Comptroller's Office; 1980 - 2006 from housing permits by county from Texas AM Real Estate Center; 2007 - 2009 from statewide Comptroller Fall Economic Forecast (2007 publication); 2010 - 2040 from Texas State Data Center Population Growth Estimates, 2041-2050 no growth assumed Skid Steer Loaders 1990 - 2004 from DFW area sales data; no growth assumed before 1990 (no si gnificant market presence before this time); 2005+ from Economy.com projections for all construction sectors (SIC 1500s - 1700s) Transportation/Sales/Services Economy. com projections for corresponding SIC
groups Bore/Drill Rigs, Cranes, Rough Terrain Forklifts, Trenchers Economy.com projections for all construction sectors (SIC 1500s - 1700s) Special Trades Construction Economy.com projections for SIC 1700 series Manufacturing Economy.com projections for corresponding SIC series Brick and Stone Economy.com projections for corresponding SIC series Concrete Operations Economy.com projections for corresponding SIC series Landscaping TX REMI data and regression between 1999 and 2013, forecast and back-cast based on census population growth rates Municipal and County Fleets, City and County Roads, Landfills Based on Texas State Data Center census population projections through 2040, linear interpolation to 2050 Utility Contractors Economy.com projections for corresponding SIC codes TxDOT Equipment No growth assumed, all years, based on TxDOT purchasing cycles

The following discusses how these growth fact or surrogates were id entified, selected, and processed for each of the 24 non-road equipment sectors. The resulting county-level growth factors have been provided to TCEQ in electron ic form for the 2004 base year for each of the sectors developed for this task.NONROAD Default Categories

The NONROAD model contains default growth factors covering th e entire period from 1970 through 2050. These default factors were kept intact in the TexN m odel for two equipment sectors – “Non-DCE” equipment and “Other DCE” equipment. Non-DCE equipment refers to all equipment categories other than diesel cons truction. These include industrial, commercial, recreational, and other equipmen t categories. Alternative gr owth factors have not been developed for the TCEQ under previous studies.

Other DCE equipment includes those equipmen t categories for which non-default profiles have not been developed under other studies. These equipment t ypes are not used in earthwork activities, and were not included in previous sa les data purchases. They include off-highway tractors, crushing and processing equipment, si gnal boards and light plan ts, concrete/industrial saws, cement and mortar mixers, plate compactor s, dumpers/tenders, tampers/rammers, “other” construction equipment, as well as all DCE less than 25 hp. While the list is extensive, most of these categories are very low hp applications , and/or specialty pieces with low population numbers. As such, these equipment categories are responsible for a very small part of the DCE inventory (estimated to be 1% or less of NOx). Therefore default population, activity, and associated growth factors from NONROAD have been retained in the TexN model for these equipment.

Agricultural DCE Applications

DCE such as crawler tractors and loaders ar e used to a limited extent in agricultural applications. In the previous version of TexN, growth for agricultural other industry groups was based on historical and projected dollar outputs at the state level, from the Texas REMI model, for the period 1999 through 2013. Alternative growth surrogates for agricu ltural activity at the county level were developed from the reporte d amount of land in farms from the 2002 Texas Agricultural Census [15]. Given the volatile natu re of crop yields and prices, it was deemed that the amount of land in production was a better surr ogate for equipment activity than agriculture sector economic output. However, land in agricu ltural production was only available every five years, from 1987 through 2002, as shown in Table 1 in Attachment E.

Linear regressions were performed using the Excel’s Forecast function and above data to estimate land in farms at the county level for the entire modeling period. In the case of decreasing acreage, trend projections were capped at 0 acres. This was occasionally the case for highly urban counties. Increasi ng acreage trends were possible for highly rural counties, and projections were capped at the to tal available county size [17]. The forecast acreage values for each year were then divided by the 2004 value for each county to obtain county-level growth factors for a 2004 base year.

Single Family Housing Construction

In the previous version of TexN, growth for single family housing construction activity was based on statewide housing permit tota ls from 1999 through 2004, and projected through 2013 using linear regression. Howe ver, given the extreme downturn in the housing market over the last two years, alternative data so urces were developed for this sector.County-level housing permit data was determined to be the best source of data for this sector, available from the Texas A&M Real Esta te Center for the years 1980 through 2006 [16]. This data set contained permit information for a ll but 23 of the 254 counties in the state, all of which were rural counties. Accordingly, ERG assumed zero single family housing development for these counties for all years. Table 2 in Attachment E presents the county-level housing permit data for this time period. The 23 rural co unties without permit data are listed below.

Borden Edwards Jeff Davis McMullen Terrell Briscoe Glasscock Jim Hogg Mills Throckmorton Concho Hartley Kenedy Roberts Zapata Crocket Hudspeth King Sterling Duval Irion Loving Stonewall

Data were missing from one or more years for 17 counties in the data set (again, all rural counties with very low housing construction act ivity). Gap filling for the missing years was performed by taking the county average for the y ears with actual data and is shown in green highlighting in Table 2 in Attachment E.

Housing permits prior to 1980 were based on ho using start totals for the southern region of the country obtained from the US Census Burea u, as shown in Table 3 in Attachment E [17]. County level permit totals from 1980 were therefore back-cast to earlier years using annual ratios from these data.

Growth for the 2007 through 2009 period was based on state level forecasts for housing starts from the Texas Comptrollers Fall 2007 Forecast [18]. The housing start data for 2007, 2008, and 2009 from this source were 129,729; 108,056; and 129,393 respectively. 10

Housing construction growth for 2010 and beyond was assumed to stabilize and follow long-term population projections. County level census projections were obtained from Texas State Data Center for th e years 2010 through 2040 [19]. 11 (The associated data file is quite large and is available from the TCEQ in electroni c format.) 2009 housing permit estimates were projected forward using the annua l county level population growth rates from this data set. Lacking other data sources, housing activity was assumed to equal 2040 estimates from 2041 through 2050.

Single family housing growth factors were developed for each county for the 2004 base year by dividing permit estimates for each year by the associated 2004 total.

Heavy-Highway Activity

The previous version of TexN used a comb ination of county level highway construction and maintenance budgets from the Texas Comptr oller’s Office and proj ected contract dollar values from McGraw Hill Construction to estima te the growth in highway construction activity.

10 It was determined that Economy.com, a potential alte rnative source of surrogate data, showed essentially no downturn for this sector during the 2006 – 2008 time period. Therefore the Comptroller data was deemed more appropriate for this sector.
11 Growth Scenario 0.5 was used based on Demographer recommendations from the web site.In order to expand the growth es timates for this sector to co ver the target period, ERG first obtained an updated list of annua l highway expenditures from the Texas Comptroller’s Office, for the period 1998 through 2006 [20]. Expenditure s were normalized to 1998 dollars using the Consumer Price Index (CPI) obtained from the Bu reau of Labor Statistics, and are presented below in Table 4 in Attachment E [21].

Attempts to extrapolate the Comptroller data using linear regression resulted in highly erratic, negative trends in key ur ban areas. Therefore highway cons truction activity prior to 1998 and after 2006 was obtained by TCEQ staff usi ng the Economy.com database [22]. Growth factors were derived at the county level fo r the 1978 – 2037 period using economic output (in real dollars) for NAICS code 2373, Highw ay Street and Bridge Construction. 12 Activity levels outside this period were assumed constant. Growth factors for the entire modeling period were then calculated as with the othe r sectors for the 2004 base year.

After development of these factors it was brought to ERG’ s attention that highway construction and maintenance budgets have been significantly influenced by rapidly rising materials costs over the past fe w years [23]. Accordingly, usi ng total budget dollars without adjusting for material cost increases will substa ntially overestimate highway activity growth in recent years. As such, ERG will provide an adju stment to the current growth factors for this sector to account for material cost inflation, using the TxDOT Highway Cost Index Report for May 2008, including the adjustments in the final it eration of the TexN model (by August 2008).

Skid Steer Loaders

In the previous version of the TexN model, growth for skid steer loaders (and all other specialty equipment) was based on historical and projected dollar outputs at the state level, from the TX REMI model. However, a review of skid steer loader sales in the Dallas/Fort Worth area indicate that these equipment underwent a dr amatic increase in popularity through the 1990s, with the increase in new sale s leveling off only around 2002, as s hown in Figure 1-1 below [24].

12 Data from the Economy.com database are considered confidential and are not presented here. All manipulation and processing of the Economy.com data were performed by authorized TCEQ personnel.Figure 1-1. Annual Skid Steer Loader Sales, 9-County DFW Area (1990-2004)

0 100 200 300 400 500 600 700 800 900

1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Source: Equipment Data Associates [24]

ERG used the above sales data as a surrogate fo r skid steer loader ac tivity for the state as a whole for the 1990 – 2004 time period. Given the unique surge in popularity of these equipment, this surrogate was deemed preferable to other options such as economic output in associated industries during this time. Since skid steer loaders were uncommon before this time, ERG assumed earlier activity was equal to 1990 levels. Activity after 2004 was assumed to follow gross output for all construction sectors. This data was obtained at the county level through 2037 by the TCEQ using the Economy.com database. County level output projections for each year through 2037 were summed across the NAICS industry codes shown in Table 1-12 (representing common users of this equipment type):

Table 1-12. Construction Sector NAICS Codes

Sector NAICS Highway Construction 2373 Residential Building Construction 2361 Non-residential Building Construction 2362 Special Trades Contractors 238B Utility System Construction 2371

Skid steer loader ac tivity beyond 2037 was assumed to equa l 2037 levels. Growth factors relative to the 2004 base year were calculated based on these data as described for other sectors above.

Other Specialty Equipment – Bore/Drill Rigs, Cranes, Rough Terrain Fo rklifts, and Trenchers

In the previous version of the TexN model, growth for other specialty equipment was based on historical and projected dollar outputs at the state level, from the TX REMI model. Unlike the skid steer loaders, the sales data available for the 9-county DFW area for theseequipment types did not show a definitive trend. Therefore it was decided to use gross economic output for all construction sectors (as shown Table 5 in Attachment E), for all available years in the Economy.com database (1978 – 2037). TCEQ st aff obtained and processed the associated data for these NAICS codes for all Texas countie s during this period, which was then converted to growth factors with a 2004 base year. No growth was assumed prior to 1978 or after 2037.

Municipal and County Fleets, City/County Road Construction, and Landfills

County level census population projections were used in the previous version of TexN to forecast and back-cast DCE activity for these sectors for the 1999 – 2013 period. ERG concluded census population continues to be the best available surrogate for these sectors. ERG used the county-level census population estimates from the Texas State Data Center to develop growth factors for the period of interest [19]. Historical pop ulation was provided for decade years from 1970 – 2000, as shown in Attachment E. Population estimates for non-decade years were estimated using linear interpolation.

Census population estimates for 2000 thr ough 2040 were based on the State Data Center’s 0.5 Scenario, and have been provided to the TCEQ in el ectronic format. Populations for 2041 through 2050 were estimated by ERG by interpolation from 2039 and 2040 values.

Other Construction Applications

The previous version of TexN utilized project dollar values from different sources, such as the TX REMI model and McGraw-Hill Construction to forecast and back-cast equipment activity for a number of differe nt DCE sectors, for the 1999 thr ough 2013 period. For this effort gross economic output data from Economy.com wa s identified as the best, most consistent growth surrogate for these sectors, consider ing the broad range of projection years (1978 – 2037), and the geographic specificity (county level estimates). Table 4-13 lists the DCE sectors and associated NAICS codes for which Economy.com data was used.

Table 1-13. DCE Sectors Utilizin g Economy.com Growth Surrogates

Sector NAICS Commercial Building Construction 2362 Utility System Construction 2371 Special Trades Contractors 238X Manufacturing 31XX – 33XX* Cement and Concrete Product Manufacturing 3273 Clay Product and Refractory Manufacturing 3271 Transportation/Sales/Services 42XX (wholesale), 44XX – 45XX (retail), 48 XX – 49XX (transportation and warehousing), 81XX (other services) * Less cement, concrete, and clay product manufacturing

TCEQ staff obtained and pr ocessed the county level gross output data from Economy.com for the above NAICS codes, and provi ded the associated growth factors for the 2004 base year.Landscaping Services / Scra p and Recycling Facilities

The previous TexN model utilized gross output for these sectors obtained from the TX REMI model for the 1999 through 2013 period. Landscaping services correspond to NAICS code 56173, and scrap-related activities to NAI CS code 562920. Unlike the Other Construction Applications listed above, it was not possible to extend the growth surrogates for these sectors beyond this time period using the Economy.com data, since queries of the database could only be performed for 4-digit NAICS codes (or higher levels of aggregation) . For this reason ERG used the TX REMI model outputs for the 1999 thro ugh 2013 period, extended by linear regression using Excel’s Forecast function for the scrap/recy cling sector. Linear regression resulted in unreasonable historical activity projections for the landscaping sector however (e.g., negative activity for certain counties in the 1970s and 1980s ). Therefore census pop ulation was used for the remaining years for this sector, to develop growth factors for these sectors.

Tables 6 and 7 in Attachment E provide the TX REMI model outputs (in 1996 dollars) for the landscaping and scrap/recy cling sectors, respectively.

TxDOT Equipment

TxDOT maintains a constant inventory of th eir non-road equipment fleet. As such, no growth (i.e., a constant equipment population) is assumed across all years for this DCE sector.

Once growth factors were obtained for all the equipment sectors, ERG applied these factors to the base year equipment populations for each sector/county combination in the TexN model. This calculation provided forecast and back-cast equipment popula tion totals for every calendar year, from 1970 through 2050. The TexN model was then modified to store the population data for every possible analysis year, bypassing the need to modify growth factors in the future. The revised mode l will lookup the correct population based on the analysis year directly input by the user , thereby avoiding recurri ng problems with SCCs that experience rapid fluctuations in their population levels. 13

1.3 Data Processing

Given the large number of model years, hp bins, and SCCs included in the NONROAD output files, em issions estimation necessarily includes a large amount of data processing and post-processing. Therefore a set of data management tools have been developed including the GUI, a database for data table storage and retr ieval, and a modified Access Reporting Utility. The following clearly documents the steps used to aggregate and combine the emission and activity data for each equipment category and fuel type within TexN.

1.3.1 TexN Data Management Tools and Processes

The TexN GUI was designed to incorporate more user-friendly features than the NONROAD m odel, accommodating the need for a finer level of emissions processing, and

13 The NONROAD model’s scrappage algorithm is not capable of accurately modeling equipment populations with highly negative growth from year to year. This situation is common with certain types of transient activities, such as heavy-highway projects and boring/drilling activities.allowing for more detailed documentation of each run. The GUI interacts with a MySQL database, which enhances the user’s ability to manage data, group runs, and document scenarios. The database was populated with all of the popula tion and related activity data described above. The database is also utilized to automatically apply post-processing adju stments as appropriate, and create output files that can be imported into the modifi ed Reporting Utility. A brief overview of the data management and emissi ons calculation process is discussed below.

The TexN GUI allows the user to group a large number of NONR OAD input files and save them to the MySQL database as a single “s cenario”. For example, the modified GUI builds a NONROAD OPT file for each county the user sele cts. Should the user choose to estimate emissions for DCE, an OPT file is built fo r each county-DCE sector combination. By performing a separate NONROAD model run for each county and DCE sector combination it is possible to apply activity and pos t-processing adjustments at the county and DCE sector level to emissions estimates. However, this approach ha s substantial implications for the number of OPT files required to estimate emissions, as is di scussed in the next section. The GUI, however, greatly facilitates building the numerous OPT files required for re gional and stat ewide modeling tasks.

The GUI interacts with the MySQL database to dynamically generate an OPT file for each run required by a scenario. For example, by specifying a particular county, analysis year, and season, an OPT file can be c onstructed containing county speci fic fuel and temperature data (which are stored in the database). Similarly, data are pulled from the database to generate county and sector specific populatio n and activity files as well. In this way the GUI populates the OPT and supporting files with the region spec ific data necessary for the NONROAD model to execute. Once the OPT and related files ar e generated, the interface executes the NONROAD model for each OPT file contained within the scenario. Once the NONROAD model is launched, the interface tracks th e progress of the current r un and launches the next run sequentially. The GUI also checks for error messages generated by the NONROAD model. If a “warning” is reported, it is reco rded in the message file, but does not affect processing. However, if an “error” is reporte d, the entire scenario is stopped and the user is presented with information on the error that occurred. All output files cr eated by the NONROAD model are retained regardless of any warning or error messages generated.

Executing NONROAD to account for county an d SCC specific data and post-processing adjustments can require a multitude of runs. Each county requires its own OPT file. In addition, DCE requires emission calculations at a sector level. There are 24 DCE sectors, each corresponding to a unique equipment activity pr ofile. (As noted above, DCE sectors include commercial building construction, utility proj ect work, and resident ial construction, among others.) Each county-DCE sector combination also requires its own OPT file. Furthermore, in order to appropriately apply te mperature, humidity, and fuel property adjustments, seasonal emissions must be calculated separately and summed together to estimate annual emissions. A summary of the number of the OPT files necessa ry for each model run within a scenario is presented in Table 1-14.Table 1-14. Required Number of NONROAD OPT Files and Model Runs for Selected Modeling Scenarios

User Selections Period Region Equipment Number of Runs* How the Number of Runs are Calculated

OSD^

or One Season One County Non-Diesel Construction Equipment (Non-DCE) 1 One for the selected county [1 segment * 1 county]

Annual One County Non-DCE 4 One for each County and Season [1 segment * 1 county * 4 seasons] OSD^

or One Season Three Counties Non-DCE 3 One for each selected county [1 segment * 3 counties]

OSD^

or One Season One County DCE 24 One for each of the 24 DCE sectors for the selected county [24 segments * 1 county]

Annual One County DCE 96 One for each of the 4 seasons and each of the 24 DCE sectors for the selected county [24 segments * 1 county * 4 seasons] OSD^

or One Season Three Counties DCE 72 One for each of the 24 DCE sectors for each of the selected counties [24 segments * 3 counties]

Annual Statewide All 25,400 One for each of the DCE sectors and one for NonDCE equipment for each county for each season [(24 + 1) SCC segments * 254 counties * 4 seasons] *Each run requires one option file and each of the ass ociated input files (e.g., population, activity, etc.) ^Ozone season day

To give an idea of run times, using a Dell Optiplex GX280 Intel® Computer with a Pentium® 4 CPU 3.00GHz with 512 MB of RAM, each run takes approximately 8 – 10 minutes to complete.

Once all of the runs for a scenario have execu ted successfully, the interface calls the postprocessing driver. The post-processing driver im ports all of the NONROAD output files into the MySQL database. The database then post-proce sses of all of the data, applying adjustment factors to the emissions estimates in the output f ile to generate the final criteria pollutant and ammonia emissions values. Post-processing app lies county specific alti tude, ground cover, and soil adjustments to emissions estimates for the appropriate SCCs. County and year specific temperature and humidity adjustments are also a pplied, along with adjustments to account for TxLED impacts in the appropriate counties, for diesel-fueled equipment. Once the postprocessing adjustments are made, the database pe rforms county-level aggregation of data by SCC and hp bin, summing population, activity, fuel -consumption, and emissions fields. Once completed, the database creates a single output file.This output file is then ready to be impor ted into the modified Reporting Utility. The TexN Reporting Utility has all of the basic functionality of the NONROAD Reporting Utility, but has been modified to accommodate ammonia emissions estimates. In addition, the TexN Reporting Utility allows the user to gene rate more reports than the NONROAD version, including emission totals by county and SCC, as well as totals by hp bin and SCC.

1.3.2 Post-Processing Adjustments

Once all of the data edits have been c ompleted and saved by the user, TexN will create the necessary Option and supporting data files for NONROAD, and batch the runs needed to model the prescribed scenario. Once the runs for a scenario have executed successfully, the GUI automatically calls the post-processing driver. The post-processing driver imports all of the NONROAD output files, generated at the by mo del year level of detail, into the MySQL database. The database then post-processes all of the data, applying adju stment factors to the emissions estimates in the output files to gene rate the final criteria pollutant and ammonia emissions values. Post-processing applies county specific adjustments to emissions estimates for the appropriate SCCs. Depending upon the SCC and county, the following adjustments may be applied within the database:

 County and year specific temperature and humidity adjustments for NOx emissions;

 Adjustments for Texas Low Emission Diesel (TxLED) impacts;

 Altitude, correcting for decreased engine efficiency at increasing elevation;

 Soil compaction, reflecting relative ea se or difficulty digging; and,

 Ground cover, reflecting relative ease or difficulty in land-c learing activity;

Once post-processing adjustments are made to the NONROAD output files, the database performs county-level aggregation of the da ta by SCC and hp range, summing population, activity, fuel-consumption, and emissions fields. Once completed, the database creates a single output file. The output file contai ned in the database is then ready to be imported into the Reporting Utility. The TexN Reporting Utility has a ll of the basic functionality of the original NONROAD utility, but has been modified to a ccommodate ammonia emissions estimates. In addition, the TexN Reporting Util ity allows the user to gene rate more reports than the NONROAD utility, including emissi on totals by county and SCC, as well as emission totals by hp and SCC.

Altitude Adjustments

Altitude adjustments are applied to all polluta nts, as well as equipment activity estimates (in hours per year), for all diesel powered equipmen t. In general, diesel engines are assumed to suffer a 1% penalty in power output, and theref ore productivity, per 1,000 f eet in altitude. In other words, an activity requiring 100 hours at sea level would require 101 hours at 1,000 in elevation. Representative altitudes for each coun ty were determined from GIS data containing altitude for each county seat [8]. For example, Anderson County has an altitude of 470 feet, and a corresponding adjustment factor of 0.47%, so all diesel equipment pollutant estimates for this county are multiplied by 1.0047 to reflect the alt itude-induced increase in diesel equipment activity.Given that the vast majority of the state is at relatively low al titude, TexN emission estimates are generally not sensitive to county altitude.

Soil and Ground Cover Adjustments

Substantial variations in c onstruction equipment productivit y, and therefore activity, can arise depending on soil and ground cover conditi ons in a given county. In a previous study, industry experts were consulted to develop activity adjustment fact ors to be applied to the DCE activity profiles, accounting for county specific c onditions [8]. Adjustments for standard soil and ground cover conditions were based on field experience and engineering judgment, and are summarized in Table 4-15. (Note these factors are only applied to DCE earthwork categories within TexN.)Table 1-15. Site Condition Activity Adjustments

Ground Cover Adjustment Factor (1.0=base conditions) Wooded lot (dense/moderate) 1.5 Small trees, shrubs, and weed 1.3 Weed and Grass 1.0 Other Varies Soil Type Adjustment Factor Good common earth (loam) 1.0 Sand/Gravel 1.0 Easy digging (moist silt/clay) 1.0 Hard digging (dry clay) 1.1 Fragmented Rock 1.2 Intact Rock 1.7 Other Varies

The above factors represent the increase in the time required to complete a certain task, relative to base case conditions, (equivalent to an in crease in work time, since engine load factors are assumed constant under all conditions). Gr ound cover adjustments are applicable to the Commercial and Residential DCE profiles, but only for equipment involved in land clearing activities (assumed to be crawler dozers). U.S. Geological Survey (USGS) data were used for determining ground cover character istics [8, 26]. The ground cover categories provided in the USGS data for Texas were mapped to one of the four standard classifications shown in Table 4- 15.

Average values for ground cover character istics were developed for each county, weighted by relative area. Areas designated as having water or impermeable/existing structures were excluded, and the relative areal extent of the remaining categories was renormalized. Weighted average adjustment fact ors specific to each county are then applied to the base case DCE profiles within TexN to acc ount for area-specific conditions.

Soil type adjustments for productivity are app licable to equipment involved in earthwork operations as well as boring/drilling tasks. For example, excavation work in areas with fragmented rock will require an additional 20 % increase in hp-hours compared to “easy digging” soil conditions. In or der to characterize soil conditions across the State, the Soil Survey Geographic Database (SSURGO) was obtained from the U.S. Natural Resource Conservation Service [25]. Three soil layers were extracted from this database, including the surface layer, the layer found at 90 cm, and the layer found at 150 cm, near or at the maximum depth of the data set, to provide a cross-section for analysis. Th e classifications of these layers were then correlated with the standard soil classifications shown in Table 4-15.

Both the spatial extent and depth of each laye r were used to develop weights for the DCE adjustments. The productivity adjustment for each layer was weighted by the relative thickness of the layers, and summed to provide a weighted average adjustment for the soil as a whole. The inverse of the resulting county- level soil adjustment factors is shown in Figure 4-2. The resulting countywide activity adju stment factors are applied to the Commercial, Residential and Utility sector DCE profiles, as well as th e Trencher and Boring/Drilling profiles.Figure 1-2. County Level Weighted Average Soil Adjustment FactorsThe DCE equipment profiles were evaluated to establish what portion of equipment activity should be subject to the soil productivi ty adjustments. The fraction of time each equipment type spends performing earthwo rk is summarized below in Table 4-16.

Table 1-16. Earthwork Weighting Factors for Soil Adjustments

DCE Sector Equipment Type Earthwork Fraction (% of time, weighted by hp-hrs) All Trencher 100% All Boring/Drilling 100% Excavator 100% Backhoe 100% Grader 49% Commercial

Crawler Dozer 40% Utility Excavator 100% Excavator 100% Residential Crawler Dozer 41%

Soil adjustments specific to each county a nd DCE sector were calculated as follows:

SCCs: 2270002030, 2270002033, 2270002036, 2270002048, 2270002066, 2270002069 DCE Sub sectors: Commercial, Utility, Boring and Drilling, Residential, Trenchers Application: Varies by sector and SCC – Commercial (2270002036, 2270002066) = Pollutant / Adj. Factor Commercial (2270002048) = Pollutant * (0.51 + 0.49/ Adj. Factor) Commercial (2270002069) = Pollutant * (0.60 + 0.40/ Adj. Factor) Residential (2270002036) = Po llutant / Adj. Factor Residential (2270002069) = Pollutant * (0.59 + 0.41 / Adj. Factor) Utility (2270002036) = Pollutant / Adj. Factor Boring and Drilling (2270002033) = Pollutant / Adj. Factor Trenchers (2270002030) = Pollutant / Adj. Factor

The weighting factors applied to the different SCCs above reflect the percent of hp-hrs a specific equipment type is involved in earthwo rk activities, as show n in Table 4-16 above.

As seen in Figure 4-2, although the largest soil adjustments occur in West Texas near the Edwards Plateau, substantial adjustments (> 10 %) are applied in all non-attainment regions across the state. However, as shown above thes e adjustments are only app lied to a small number of SCCs in a few DCE sectors. Therefore, while the activity adjustments can be substantial for any particular county/SCC/DCE sector combinati on, the overall impact on emissions is relatively small.

Ground cover adjustments were only applie d to crawler tractor s operating in the Commercial and Residential DCE s ectors. In this case each po llutant is multiplied by (0.955 + 0.045 x county specific ground cover adjustment). While the ground cover adjustments can be substantial for crawler tractors operating in heavily wooded areas such as East Texas, theadjustment is only this one equipment type operating within two of the DCE sectors. Accordingly, overall emissions are not particul arly sensitive to these cover adjustments.

Temperature and Humidity NOx Adjustments for Diesel Engines

TCEQ identified additional temp erature and humidity correction factors for adjustment of NOx emissions from diesel engines [14]. The NO x adjustment equations developed in this study are a function of temperature, humidity, and at mospheric pressure. Using the climate data discussed in Section 4.2.2, temperature and humid ity adjustment factor s were calculated for diesel equipment operating in each county in the St ate, for each season and meteorological year. The application of these adjustme nt factors is summarized below.

16) Adjustments are applied to all di esel engines (SCC = 227XXXXXXX) 17) Adjustments are only applied to NOx emissions 18) Adjustments also depend upon technology type distributions, as determined by Analysis Year 19) Inputs to the adjustment equa tions include the following:

 County Average Temperature (T – season and meteorological yearspecific, from Climate Data – in degrees Fahrenheit)

 County Relative Humidity (RH – season and meteorological year-specific, from Climate Data – in percent)

 County Atmospheric Pressure (P – in mill bars, or mb) 14

20) Adjustments utilize absolute humidity (H), which is calculated as follows:

H = [RH x 38.017 x ea] / [P – 6.112 x ea] where a = [9.8245 x (T – 32)] / [0.556 x (T – 32) + 243.5]

21) There are two adjustment equations – one e quation is used for naturally-aspirated engines, another for turbocharged engines.

Naturally-Aspirated Engine Adjustment: 1 + 0.001368 x (0.556 x (T - 32) – 29.444) – 0.01512 x (H – 10.71)

Turbo-charged Engine Adjustment: 1 + 0.00446 x (0.556 x (T – 32) - 25) – 0.018708 x (H – 10.71)

22) The fraction of naturally-aspirated and tu rbocharged engines depends upon engine model year and hp bin. Rela tive fractions were estimated based on the number of engine entries in EPA’s cer tification database. Data we re available electronically

14 Average station pressure was found to vary by insignificant amounts over time. For the purposes of this calculation, annual average pressure for each station was calculated for the 2000 meteorological year.from EPA for model years 1998 through 2006. 15 The weighting factors applied to the two different adjustment equations correspond to the re lative fraction of naturally-aspirated to turbocharged engi nes for a given model year, summarized in Table 4-17 below:

Table 1-17. Ratio of Turbo to Naturally-Aspirated Models for Diesel Engines by hp and Model Year

Model Year

hp Range 1999 (and older) 2000 2001 2002 2003 2004 2005+ < 25 0% 0% 0% 0% 0% 0% 0% 25 – 50 10% 14% 15% 17% 15% 14% 18% 50 - 100 28% 28% 28% 28% 47% 55% 55% 100 – 175 63% 84% 84% 84% 98% 98% 98% 175+ 100% 100% 100% 100% 100% 100% 100%

23) Given this information TexN first ca lculates the naturally-aspirated and turbocharged factors for each county a nd season, then weights and sums the factors using the relative fractions given above for each hp bin and model year, and applies the final weighted factors to the NOx emissions value by the appropriate hp bin and model year in the by model year exhaust file (BMX file). 16

The above adjustments can result in subs tantial changes to diesel NOx emission estimates. For example, for a 2005 Analysis Year, from a baseline of 80 degrees F and 50% relative humidity, a 10% increase in humidity results in a 4% reducti on in NOx emissions. However, although increasing temperature and decr easing relative humidity will tend to increase NOx emissions from diesel engines, this eff ect is offset by NONROA D’s downward adjustment of NOx emissions from ga soline 4-stroke engines.

Adjustments for Emission Controls

Various control programs have been implem ented to reduce emissions from non-road engines. Federal controls, such as the introduction of new emission standards, are accounted for by the NONROAD model. While evaporative refue ling (Stage II) VOC emission controls can be modeled by NONROAD, these emissions are categori zed as area sources by the TCEQ. For this reason any Stage II emission control benefits a ssociated with non-road engine refueling are excluded from TexN to avoid double counting.

15 Data from EPA’s certification record s are not sales-weighted, and therefore may not represent the actual in-use distribution of naturally-aspirated and turbocharged engines. However, sales data is considered proprietary by manufacturers, and was not available for this analysis.
16 The fraction of naturally-aspirated and turbocharged engines depends upon engine model year and hp bin, so adjustments must be applied to NONROAD’s by model year exhaust (BMX) output file. This file provides emission estimates for each SCC and hp bin combination, as well as by model year and engine technology type. Since there are no NOx emissions in the by model year evaporative emissions (BMV) file, no adjustments applied there.The introduction of TxLED in certain Te xas counties is not accounted for by the NONROAD model, and is addre ssed during TexN post-processing. Specifically, NOx emissions from diesel engines were reduced by 6.2% beginning in February of the 2006 calendar year, for the 110 counties affected by the TxLED program . TxLED was implemented January 31, 2006. TexN has refined the dates for application of Tx LED credits to emissions estimates beginning in February 2006 and beyond, as described below.

24) The TxLED “flag” is now activated for 2006 and later analsysis years, for the 110 counties. 25) Annual modeling scenarios for 2007 and beyond receive the full credit of 6.2% NOx reduction applied to all diesel emissions in TxLED counties. 26) If an annual modeling scen ario is selected for the 2006 calendar year, the full 6.2% diesel NOx reduction is applied to the spring, summer, and fall season calculations. 27) Winter season diesel NOx emissions for 2006 are reduced by 4.1%, assuming adjustments for 2 of the 3 winter months (Jan, Feb, and Dec of 2006). 28) Ozone-season daily scenarios for the 2006 calendar year receive the full 6.2% diesel NOx reduction adjustment.

A detailed example showing the steps involved in the TexN emission calculation process is provided in Attachment F.

Other rules and regulations that effect non -road engines include multiple Memoranda of Understanding and other agreements with specific fleets in different nonattainment areas, such as airport ground support equipment (GSE) and Port activities. Texas Emission Reduction Program (TERP) projects also fall under this category. Howe ver, these fleet-level c ontrol initiatives have to be modeled using fleet-specific equipment a nd activity profiles. Similarly, emissions from unusual construction projects that have been prof iled on an individual basis previously (such as the construction of three large liquid natural gas depots on the Gulf Coast), must also be modeled on a fleet-specific basis to account for their inventory impacts. As such the effects of these programs and initiatives are not reflected in TexN outputs.

1.3.3 Calculation of Ammonia Emissions

The NONROAD model does not provide estimates for ammonia emissions. In order to provide am monia estimates using TexN, a list of available ammonia em ission factors for the different non-road mobile engine fuel types, including diesel, gasoline, and gaseous fuels (propane and natural gas), were identified and documented [14]. A literature review was performed, and contacts were made with air quality researchers from EPA’s Office of Transportation and Air Quality (OTAQ), the Calif ornia Air Resources Board (ARB) and others to identify available data sources. A detail ed web search was also conducted to identify additional sources of emissions test data and analysis. Avai lable data were evaluated for applicability to non-road engine applications, and emission factor s were processed and adjusted to account for the impact of futu re engine technology impacts to the extent possible. Emission factors in TexN are expressed in terms of grams per hp-hour of engine use, and/or grams per gallon of fuel consumption.Only a limited amount of information was id entified regarding ammonia emissions from non-road engines. An attempt was made to iden tify the most representative data, considering fuel and engine types, as well as the infl uence of future emission standards on control technologies. The ammonia emission factors id entified can be combined with activity data outputs from NONROAD to estimate mass emissi ons for each SCC and county in Texas. Ammonia is estimated within TexN in tons for all SCCs.

There are four ammonia emission factors in Te xN: one for diesel engines, one for spark ignition engines (gasoline and gaseous fuel) without three-way catalysts (TWCs), one for gasoline engines with TWCs, and one for natura l gas/LPG engines with TWCs. The emission factors and corresponding technology type s are presented in Table 4-18 below.

Table 1-18. Ammonia Emission Factors Used in TexN

Engine Type Emission Factor Units Diesel 0.00162 g/hp-hr Gasoline w/ TWC 0.0690 g/hp-hr CNG/LPG w/ TWC 0.1030 g/hp-hr Spark Ignition w/out TWC 0.15 g/gal

Note that all emission factor s are in g/hp-hr except for spark ignition engines without TWCs, which is in g/gal. Emissions for SCC/technology type combinations with emission factors in g/hp-hr are calculated in TexN by mu ltiplying the factor by the average hp value, the load factor, and the activ ity value in the BMX file. Results are then converted from grams to tons for output. For those SCC/Technology Type co mbinations expressed in g/gal, emissions are calculated by multiplying the emission factor by the fuel consumption value in the BMX file, then multiplying by 1.1023e-6 to convert from grams to tons.

2.0 

## References

1. User’s Guide for the Final NONRO AD2005 Model, EPA420-R-05-013, December 2005, http://www.epa.gov/otaq/nonrdmdl.htm 2. NONROAD2005 Emission Factor Model, available from http://www.epa.gov/otaq/nonrdmdl.ht m, last validated 11-18-2006. 3. Eastern Research Group, Sampling and Laborat ory Analysis of Retail Fuel for Selected Texas Cities, prepared for Peter Ogbeide, Texas Commission on Environmental Quality, August 29, 2003. 4. Eastern Research Group, Sampling and Laborat ory Analysis of Retail Fuel for Selected Texas Cities – Summer 2004, prepared fo r Peter Ogbeide, Texas Commission on Environmental Quality, August 31, 2004. 5. Eastern Research Group, Sampling and Laborat ory Analysis of Retail Fuel for Selected Texas Cities – Summer 2005, prepared fo r Peter Ogbeide, Texas Commission on Environmental Quality, August 31, 2005.6. Eastern Research Group, Sampling and Laborat ory Analysis of Retail Fuel for Selected Texas Cities – Winter 20 06, prepared for Peter Ogbeide, Texas Commission on Environmental Quality, April 30, 2006. 7. Texas A&M University Energy Systems Laboratory, http://energysystems.tamu.edu/sb5/da ta.html, last validated 11-22-06. 8. Eastern Research Group, Ozone Science a nd Air Modeling Research Project H43T163: Diesel Construction Equipment Activity and Emissions Estimates for the Dallas/Ft. Worth Region, prepared for The Houston A dvanced Research Center, August 31, 2005. 9. Eastern Research Group, Statewide Diesel Construction Equipment Inventory, prepared for the Texas Commission on Environmental Quality, August 31, 2005. 10. Eastern Research Group, Nonroad Mobile Source Emissions Invent ory Development for the Houston-Galveston-Brazoria Area, submitted to the Houston-Galveston Area Council, July 28, 2006. 11. Eastern Research Group, Data Collection, Sa mpling and Emissions Inventory Preparation Plan for Selected Commercial and Industrial Equipment: Phase II, Final Report, prepared for the Texas Commission on Environmental Quality, August 31, 2005. 12. Eastern Research Group, Development of Commercial Lawn a nd Garden Emissions Estimates for the State of Texas and Sel ected Metropolitan Areas, prepared for Texas Commission on Environmental Quality, November 24, 2003. 13. Eastern Research Group, Recreational Mari ne Emissions Inventory, prepared for the Texas Commission on Environm ental Quality, August 28, 2002. 14. Eastern Research Group, Nonroad Amm onia Emissions Inventory Development, prepared for Texas Commission on E nvironmental Quality, November 24, 2006 15. EPA Office of Transportation and Air Qu ality, User’s Guide to MOBILE6.1 and 6.2, http://www.epa.gov/otaq/models/mobile 6/420r03010.pdf, last validated 11-22-06. 16. Texas A&M Real Estate Ce nter, Texas County Building Permit Activity Data, from http://recenter.tamu.edu/data/bpc/. 17. U.S. Census Bureau, New Privately Owned Housing Units Started: Annual Data, http://www.census.gov/ const/startsan.pdf. 18. Texas Comptroller of Public Accounts, Fall 2007 Economic Forecast, Texas Economic Detail, from http://www.window.state.tx.us/ecodata/fcs t07fall/fall07economiccalendar.html. 19. Texas State Data Center, 0.5 Growth Scenario, http://txsdc.utsa.edu/tpepp/2004projections/. 20. Texas Comptroller of Public Accounts, Texas State Expenditures by County, from http://www.window.state.tx.us/taxbud/expbyco/. 21. Bureau of Labor Statistics, Consumer Pr ice Index, All Urban Consumers, South Region, from http://data.bls.gov/PDQ/servlet/SurveyOutput Servlet?data_tool=dropmap&series_id=CU UR0300SA0,CUUS0300SA0 - all c onsumers, South Region. 22. Personal communication with Anusuya Iyer, TCEQ, April 25, 2008. 23. Bob Lanham, Vice President Williams Brothe rs Construction, Houston Texas, personal communication May 23, 2008. 24. Equipment Data Associates, Skid Steer Lo ader Sales Records through 2005, taken from Eastern Research Group, “Statewide Dies el Construction Equipment Inventory”, prepared for the Texas Commission on Environmental Quality, August 31, 2005, p. 3-36.25. Natural Resource Conservation Service, http://www.ncgc.nrcs.usda.gov/products /datasets/ssurgo/description.html. 26. U.S. Geological Survey, http://edc.usgs.gov/geodata/.27. Environmental Protection Agency, http://www.epa.gov/fedrgstr/EPAAIR/2004/January/Day-12/a458.pdf 28. Environmental Protection Agen cy, 40 CFR 89.1003(a)(1)(i) and http://www.epa.gov/nonroad-d iesel/regulations.htm 29. Environmental Protection Agency, http: //www.epa.gov/nonroad-dies el/frm1998/nr-fr.pdf 30. Environmental Protection Agency, h ttp://www.epa.gov/otaq/regs/nonroad/equipld/hhsfrm/f00007.pdf 31. Environmental Protection Agency, http://www.epa.gov/otaq/largesi.htm 32. Environmental Protection Agency, h ttp://www.epa.gov/nonroa d-diesel/2004fr.htm 33. Environmental Protection Agency, http://www.epa.gov/otaq/models/nonrdmdl/nonrdmdl2005/420r05019.pdf 34. Environmental Protection Agency, http://www.epa.gov/otaq/models/nonrdmdl/nonrdmdl2004/420p04009.pdfAttachment B County Level Fuel SpecificationsTable B-1. Summertime Gasoline

2002 County RVP Sulfur % Oxy Wt % Brazoria 6.80 0.0162 1.75 Chambers 6.80 0.0162 1.75 Fort Bend 6.80 0.0162 1.75 Galveston 6.80 0.0162 1.75 Harris 6.80 0.0162 1.75 Liberty 6.80 0.0162 1.75 Montgomery 6.80 0.0162 1.75 Waller 6.80 0.0162 1.75

2008+ County RVPSulfur % Oxy Wt % Brazoria 6.8 0.00330 2.1 Chambers 6.8 0.00330 2.1 Fort Bend 6.8 0.00330 2.1 Galveston 6.8 0.00330 2.1 Harris 6.8 0.00330 2.1 Liberty 6.8 0.00330 2.1 Montgomery 6.8 0.00330 2.1 Waller 6.8 0.00330 2.1Table B-2. Winter time Gasoline

2002 County RVP Sulfur % Oxy Wt % Brazoria 11.3 0.0259 3.5 Chambers 11.3 0.0259 3.5 Fort Bend 11.3 0.0259 3.5 Galveston 11.3 0.0259 3.5 Harris 11.3 0.0259 3.5 Liberty 11.3 0.0259 3.5 Montgomery 11.3 0.0259 3.5 Waller 11.3 0.0259 3.5

2008+ County RVP Sulfur % Oxy Wt % Brazoria 11.3 0.00300 3.5 Chambers 11.3 0.00300 3.5 Fort Bend 11.3 0.00300 3.5 Galveston 11.3 0.00300 3.5 Harris 11.3 0.00300 3.5 Liberty 11.3 0.00300 3.5 Montgomery 11.3 0.00300 3.5 Waller 11.3 0.00300 3.5

Table B-3. Diesel Fuel Sulfur Levels (weight %)

County 1999 - 2003 2004 2005 2006-2009 2010+ Brazoria 0.0307 0.0402 0.0351 0.0351 0.0015 Chambers 0.0307 0.0402 0.0412 0.0412 0.0015 Fort Bend 0.0307 0.0402 0.0351 0.0351 0.0015 Galveston 0.0307 0.0402 0.0351 0.0351 0.0015 Harris 0.0307 0.0402 0.0351 0.0351 0.0015 Liberty 0.0307 0.0402 0.0412 0.0412 0.0015 Montgomery 0.0307 0.0402 0.0351 0.0351 0.0015 Waller 0.0307 0.0402 0.0351 0.0351 0.0015Table B-4. Historical Census Populati on by County for 8-County HGB Area (1970 / 80 / 90 / 2000)

County 1970 1980 1990 2000 Brazoria 108,312 169,587 191,707 241,767 Chambers 12,187 18,538 20,088 26,031 Fort Bend 52,314 130,846 225,421 354,452 Galveston 169,812 195,940 217,399 250,158 Harris 1,741,912 2,409,547 2,818,199 3,400,578 Liberty 33,014 47,088 52,726 70,154 Montgomery 49,479 128,487 182,201 293,768 Waller 14,285 19,798 23,390 32,663

Source: Texas State Data CenterAttachment C TexN Emission Calculation Example2-1 The following provides an example illustrating the detailed calculation steps within the NONROAD model, as well as the post-processing adjustments applied by TexN. The derivation and use of each parameter in the fundamental em ission equation (shown belo w) are discussed, as well as the application of the approp riate locality specific adjustments.

Fundamental Emissions Equation:

Emissions p

/yr = ∑ (MYR) ∑ (HP) Pop * Power * LF * A * EF p
Where: Pop = Number of engines Power = Average hp (for specific hp group) LF = Load factor (% of rated power) A = Activity (hr/year) EF p = Emissions for pollutant p (grams/bhp-hr) ∑ (HP) = summation over each equipment hp group ∑ (MYR) = summation over each equipment model year

The example calculation is conducted for NOx emissions for the following scenario:

 County – Harris

 Equipment Type – Diesel Trenchers (SCC = 2270002030)

 Analysis Year – 2050

 Period – Ozone Season Weekday

In order to walk through the example calcula tion we recommend you run a TexN scenario for these conditions.

Step 1 – Identify NONROAD Input and TexN Adjustment Parameters . First open the TexN scenario you developed for the above conditions . This will allow you to identify the default input and adjustment parameters used within the model. From the Population Tab identify average hp, useful life (in hrs) and population for each hp bin with non-zero populations. From the Activity Tab identify the load factor and activ ity in hours per year. And from the Fuel and Climate Tab identify the average summertime te mperature in degrees Fa hrenheit, and relative humidity (typical meteorological year assumed) . These input parameters are listed below:

Population Tab hp bin avg. hp useful life population (2050) 17 25 – 50 hp 34.1 2,500 hrs 2,172.64 50 – 75 hp 61.02 4,667 hrs 491.01 75 – 100 hp 86.75 4,667 hrs 610.22

Activity Tab load factor activity 0.59 1,308 hrs/yr

17 These figures correspond to 2050 population projections.2-2 Fuel and Climate average temperature relative humidity atmospheric pressure (mb) 18
81.1 °F 75% 1,013.21

Step 2 – Determine the Model Year Distribution for Each HP Bin . NONROAD applies its default scrappage and growth curves in order to allocate the population totals for each hp bin across model years. To develop these distributions, firs t calculate the median life in years for diesel trenchers as shown below.

Median Life in years (< 50 hp) = Median life in hours / (activity in hours/yr x load factor) = 2,500 / (1,306 x 0.59) = 3.24 years

Median Life in years (> 50 hp) = 4,667 / (1,306 x 0.59) = 6.05 years

Next, the default scrappage curve must be modi fied to provide the fr action of median life expressed in terms of engine age, as shown in Table F-1 below. The age distributions shown in the table are calculated by simply multiplying the fraction of median life value by the median life expressed in years (3.24 years for engines < 50 hp, and 6.05 years for engines >= 50 hp).

Table C-1. Default Scrappage Curve Expressed in Years of Age (Trenchers)

Fraction of Median Life Cumulative % Scrapped Incremental % Scrapped Age Distribution (<50 hp) Age Distribution (>50 hp) 0 0 0 0 0 0.0294 0.5 0.5 0.095 0.178 0.0588 1 0.5 0.190 0.356 0.08705 1.5 0.5 0.282 0.526 0.1153 2 0.5 0.374 0.697 0.14235 2.5 0.5 0.461 0.861 0.1694 3 0.5 0.549 1.024 0.19535 3.5 0.5 0.633 1.181 0.2213 4 0.5 0.717 1.338 0.24615 4.5 0.5 0.797 1.489 0.271 5 0.5 0.878 1.639 0.29475 5.5 0.5 0.955 1.783 0.3185 6 0.5 1.032 1.926 0.3412 6.5 0.5 1.105 2.063 0.3639 7 0.5 1.179 2.201 0.3856 7.5 0.5 1.249 2.332 0.4073 8 0.5 1.319 2.463 0.42795 8.5 0.5 1.386 2.588 0.4486 9 0.5 1.453 2.713 0.4683 9.5 0.5 1.517 2.832 0.488 10 0.5 1.581 2.951

18 Atmospheric pressure is not displayed on the Fuel and Climate Tab, but is maintained in one of the TexN lookup tables accessible by the TexN database administrator.2-3 Fraction of Median Life Cumulative % Scrapped Incremental % Scrapped Age Distribution (<50 hp) Age Distribution (>50 hp) 0.5067 10.5 0.5 1.641 3.064 0.5254 11 0.5 1.702 3.177 0.5432 11.5 0.5 1.760 3.285 0.561 12 0.5 1.817 3.393 0.5779 12.5 0.5 1.872 3.495 0.5948 13 0.5 1.927 3.597 0.6108 13.5 0.5 1.979 3.694 0.6268 14 0.5 2.031 3.791 0.6419 14.5 0.5 2.079 3.882 0.657 15 0.5 2.128 3.973 0.6713 15.5 0.5 2.175 4.060 0.6856 16 0.5 2.221 4.146 0.69905 16.5 0.5 2.265 4.228 0.7125 17 0.5 2.308 4.309 0.7252 17.5 0.5 2.349 4.386 0.7379 18 0.5 2.390 4.462 0.7498 18.5 0.5 2.429 4.534 0.7617 19 0.5 2.468 4.606 0.77285 19.5 0.5 2.504 4.674 0.784 20 0.5 2.540 4.741 0.79445 20.5 0.5 2.574 4.804 0.8049 21 0.5 2.607 4.868 0.81465 21.5 0.5 2.639 4.927 0.8244 22 0.5 2.671 4.986 0.83345 22.5 0.5 2.700 5.040 0.8425 23 0.5 2.729 5.095 0.85095 23.5 0.5 2.757 5.146 0.8594 24 0.5 2.784 5.197 0.8672 24.5 0.5 2.809 5.244 0.875 25 0.5 2.835 5.292 0.8822 25.5 0.5 2.858 5.335 0.8894 26 0.5 2.881 5.379 0.89605 26.5 0.5 2.903 5.419 0.9027 27 0.5 2.924 5.459 0.90875 27.5 0.5 2.944 5.496 0.9148 28 0.5 2.964 5.532 0.92035 28.5 0.5 2.981 5.566 0.9259 29 0.5 2.999 5.599 0.93095 29.5 0.5 3.016 5.630 0.936 30 0.5 3.032 5.660 0.94055 30.5 0.5 3.047 5.688 0.9451 31 0.5 3.062 5.716 0.9492 31.5 0.5 3.075 5.740 0.9533 32 0.5 3.088 5.765 0.957 32.5 0.5 3.100 5.787 0.9607 33 0.5 3.112 5.810 0.96395 33.5 0.5 3.123 5.8302-4 Fraction of Median Life Cumulative % Scrapped Incremental % Scrapped Age Distribution (<50 hp) Age Distribution (>50 hp) 0.9672 34 0.5 3.133 5.849 0.9701 34.5 0.5 3.143 5.867 0.973 35 0.5 3.152 5.884 0.9755 35.5 0.5 3.160 5.899 0.978 36 0.5 3.168 5.914 0.9802 36.5 0.5 3.175 5.928 0.9824 37 0.5 3.183 5.941 0.9843 37.5 0.5 3.189 5.953 0.9862 38 0.5 3.195 5.964 0.9878 38.5 0.5 3.200 5.974 0.9894 39 0.5 3.205 5.983 0.9907 39.5 0.5 3.209 5.991 0.992 40 0.5 3.214 5.999 0.9931 40.5 0.5 3.217 6.006 0.9942 41 0.5 3.221 6.012 0.99505 41.5 0.5 3.223 6.018 0.9959 42 0.5 3.226 6.023 0.9966 42.5 0.5 3.229 6.027 0.9973 43 0.5 3.231 6.031 0.9978 43.5 0.5 3.232 6.034 0.9983 44 0.5 3.234 6.037 0.99865 44.5 0.5 3.235 6.039 0.999 45 0.5 3.236 6.041 0.99925 45.5 0.5 3.237 6.043 0.9995 46 0.5 3.238 6.045 0.99965 46.5 0.5 3.238 6.045 0.9998 47 0.5 3.239 6.046 0.99985 47.5 0.5 3.239 6.047 0.9999 48 0.5 3.239 6.047 0.99995 49 1 3.239 6.047 1 50 1 3.240 6.048 1.00005 51 1 3.240 6.048 1.0001 52 1 3.240 6.048 1.00015 52.5 0.5 3.240 6.048 1.0002 53 0.5 3.240 6.049 1.00035 53.5 0.5 3.241 6.050 1.0005 54 0.5 3.241 6.051 1.00075 54.5 0.5 3.242 6.052 1.001 55 0.5 3.243 6.054 1.00135 55.5 0.5 3.244 6.056 1.0017 56 0.5 3.245 6.058 1.0022 56.5 0.5 3.247 6.061 1.0027 57 0.5 3.248 6.064 1.0034 57.5 0.5 3.251 6.068 1.0041 58 0.5 3.253 6.072 1.00495 58.5 0.5 3.256 6.077 1.0058 59 0.5 3.258 6.0832-5 Fraction of Median Life Cumulative % Scrapped Incremental % Scrapped Age Distribution (<50 hp) Age Distribution (>50 hp) 1.0069 59.5 0.5 3.262 6.089 1.008 60 0.5 3.265 6.096 1.0093 60.5 0.5 3.270 6.104 1.0106 61 0.5 3.274 6.112 1.0122 61.5 0.5 3.279 6.121 1.0138 62 0.5 3.284 6.131 1.0157 62.5 0.5 3.290 6.142 1.0176 63 0.5 3.297 6.154 1.0198 63.5 0.5 3.304 6.167 1.022 64 0.5 3.311 6.181 1.0245 64.5 0.5 3.319 6.196 1.027 65 0.5 3.327 6.211 1.0299 65.5 0.5 3.336 6.228 1.0328 66 0.5 3.346 6.246 1.03605 66.5 0.5 3.356 6.266 1.0393 67 0.5 3.367 6.285 1.043 67.5 0.5 3.379 6.308 1.0467 68 0.5 3.391 6.330 1.0508 68.5 0.5 3.404 6.355 1.0549 69 0.5 3.417 6.380 1.05945 69.5 0.5 3.432 6.407 1.064 70 0.5 3.447 6.435 1.06905 70.5 0.5 3.463 6.465 1.0741 71 0.5 3.480 6.496 1.07965 71.5 0.5 3.498 6.529 1.0852 72 0.5 3.516 6.563 1.09125 72.5 0.5 3.535 6.599 1.0973 73 0.5 3.555 6.636 1.10395 73.5 0.5 3.576 6.676 1.1106 74 0.5 3.598 6.716 1.1178 74.5 0.5 3.621 6.760 1.125 75 0.5 3.644 6.803 1.1328 75.5 0.5 3.670 6.851 1.1406 76 0.5 3.695 6.898 1.14905 76.5 0.5 3.722 6.949 1.1575 77 0.5 3.750 7.000 1.16655 77.5 0.5 3.779 7.055 1.1756 78 0.5 3.808 7.109 1.18535 78.5 0.5 3.840 7.168 1.1951 79 0.5 3.872 7.227 1.20555 79.5 0.5 3.905 7.291 1.216 80 0.5 3.939 7.354 1.22715 80.5 0.5 3.975 7.421 1.2383 81 0.5 4.011 7.489 1.2502 81.5 0.5 4.050 7.561 1.2621 82 0.5 4.089 7.633 1.2748 82.5 0.5 4.130 7.7092-6 Fraction of Median Life Cumulative % Scrapped Incremental % Scrapped Age Distribution (<50 hp) Age Distribution (>50 hp) 1.2875 83 0.5 4.171 7.786 1.30095 83.5 0.5 4.214 7.868 1.3144 84 0.5 4.258 7.949 1.3287 84.5 0.5 4.304 8.035 1.343 85 0.5 4.351 8.122 1.3581 85.5 0.5 4.400 8.213 1.3732 86 0.5 4.449 8.304 1.3892 86.5 0.5 4.500 8.401 1.4052 87 0.5 4.552 8.498 1.4221 87.5 0.5 4.607 8.600 1.439 88 0.5 4.662 8.702 1.4568 88.5 0.5 4.719 8.810 1.4746 89 0.5 4.777 8.918 1.4933 89.5 0.5 4.838 9.031 1.512 90 0.5 4.898 9.144 1.5317 90.5 0.5 4.962 9.263 1.5514 91 0.5 5.026 9.382 1.57205 91.5 0.5 5.093 9.507 1.5927 92 0.5 5.160 9.632 1.6144 92.5 0.5 5.230 9.763 1.6361 93 0.5 5.300 9.894 1.6588 93.5 0.5 5.374 10.032 1.6815 94 0.5 5.447 10.169 1.70525 94.5 0.5 5.524 10.313 1.729 95 0.5 5.601 10.456 1.75385 95.5 0.5 5.682 10.606 1.7787 96 0.5 5.762 10.757 1.80465 96.5 0.5 5.846 10.914 1.8306 97 0.5 5.930 11.071 1.85765 97.5 0.5 6.018 11.234 1.8847 98 0.5 6.106 11.398 1.91295 98.5 0.5 6.197 11.569 1.9412 99 0.5 6.289 11.739 1.9706 99.5 0.5 6.384 11.917 2 100 0.5 6.479 12.095

The above fractions were then aggregated by engi ne age in year increments to determine the fraction of engines in each year (see Table F-2 below).2-7 Table C-2. Remaining Frac tion of Engines by Age

Age < 50 hp > 50 hp 1 0.95 0.98 2 0.87 0.94 3 0.71 0.90 4 0.20 0.85 5 0.10 0.78 6 0.03 0.60 7 0.00 0.24 8 0.00 0.16 9 0.00 0.11 10 0.00 0.07 11 0.00 0.04 12 0.00 0.01

In order to determine the 2050 model year distri bution, the fractions presented in Table Y must be combined with annual equipment sales estimat es over the previous 6 years, in the case of engines < 50 hp, and over the previous 12 years, in the case of engines >= 50 hp. The annual growth in sales can be calculated from NONROAD’s default growth file, nation.grw . From this file we identify the last two indicator values fo r the diesel construction indicator code (021), as show below.

2025 - 1,927 2045 - 2,569

The NONROAD model uses these two data points to linearly extrapolate annual sales growth rates up to 2050. Annual growth rates for the period from 2025 through 2050 are therefore calculated as [(2,569 – 1,927) / (2045 – 2025)] / 1,000 = 3.21%. 19 Therefore equipment sales totals for units of age X are related to sales totals in the year 2050 (age 1) by the following equation:

Sales age x = Sales age 1 / [1 + (x – 1) (0.0321)] = Sales age x / a x

The values for ax are shown below in Table F-3.

19 The difference between the indicator code values are divided by the 1996 base year value of 1,000 – also obtained from the nation.grw file.2-8 Table C-3. Sales Adjustment Factors by Age

Age a (x) 1 1.000 2 1.032 3 1.064 4 1.096 5 1.128 6 1.161 7 1.193 8 1.225 9 1.257 10 1.289 11 1.321 12 1.353

Dividing the total equipment population for each hp bin by the sum of the ratios of the remaining equipment fraction (Table F-2) and the sales ad justment factors (Table F-3) allows us to calculate the equipment sales totals for units so ld in 2050 (age 1) for each hp bin. The general equation for a given hp bin is shown below, with the summation over all equipment ages with non-zero remaining fractions.

Sales age 1 = Total Pop / ∑ (Remaining Fraction x / a x )

The resulting 2050 sales totals (age = 1) are shown in Table F-4 below.

Table C-4. 2050 (Age 1) Sales Totals by HP Bin

< 50 hp 793.4623 50 - 75 hp 94.15786 75-100 hp 117.0177

These age 1 sales totals are then divided by the product of the sales adju stment factor and the remaining fraction by year to obtain the model year distribution for each hp bin, as shown in Table F-5.2-9 Table C-5. Model Year Distribution by HP Bin

Yr < 50 hp 50 - 75 hp 75-100 hp 1 749.82 91.80 114.09 2 665.00 85.76 106.58 3 529.37 79.63 98.96 4 141.13 73.00 90.73 5 66.80 65.09 80.89 6 20.51 48.68 60.50 7 0.00 18.55 23.06 8 0.00 12.30 15.29 9 0.00 8.24 10.24 10 0.00 5.11 6.36 11 0.00 2.49 3.10 12 0.00 0.35 0.43 Total 2,172.64 491.01 610.22

Step 3 – Determine Emission Factors by HP Bin and Age . First, determine the technology mix for trenchers in 2050. In the tech-exh.dat file we see that di esel engine sales (SCC 227XXXXXXX) in the 25 – 50, and 50 – 75 hp bins are designated 100% “T4” starting shortly after 2010. Therefore by 2050 100% of all in-use tren cher engines are assumed to be T4. Similarly all in-use trenchers in the 75 – 100 hp range are assumed to be T4N by 2050. Next, identify the zero-hour NOx emission factors in the exhnox.emf file for the appropriate hp bin and technology type. These factors are shown below in Table F-6.

Table C-6. Zero-Hour NOx Dies el Emission Factors (2050)

HP Bin g/hp-hr Tech Type < 50 hp 3.00 100% T4 50 - 75 hp 3.00 100% T4 75-100 hp 0.28 100% T4N

Next, identify the associated NO x deterioration factors by tech nology type. These values are provided in the exhnox.det file. Deterioration factors are multiplicative to the zero-hour factors, and are calculated as follows:

DF = 1 + A × engine age b

In the above equation engine age is e xpressed as a fraction of median life.

For technology types T4 and T4N, A = 0.008 and b = 1, translating to a ve ry low deterioration rate for these engines. In addi tion, deterioration is capped once th e engine age equals the median life of the engine. By calculating engine age in terms of the fracti on of median life (hrs/yr x yrs x load factor / median life in hours), and subs tituting this value into the above equation, a2-10 separate deterioration factor can be calculated for each engine age of interest (in years), as shown in Table F-7.

Table C-7. NOx Deterioration Factors by Model Year (2050 Scenario)

Model Yr < 50 hp >= 50 hp 2050 1.0025 1.0013 2049 1.0049 1.0026 2048 1.0074 1.0040 2047 1.0080 1.0053 2046 1.0080 1.0066 2045 1.0080 1.0079 2044 1.0080 1.0080 2043 1.0080 1.0080 2042 1.0080 1.0080 2041 1.0080 1.0080 2040 1.0080 1.0080 2039 1.0080 1.0080

By multiplying the zero-hour fact ors in Table F-6 by the deterior ation factors above we obtain the age-dependent emission factors, shown in Table F-8.

Table C-8. NOx Emission Fact ors by Model Year (g/hp-hr)

Model Yr < 50 hp 50 - 75 hp 75-100 hp 2050 3.007 3.004 0.280 2049 3.015 3.008 0.281 2048 3.022 3.012 0.281 2047 3.024 3.016 0.281 2046 3.024 3.020 0.282 2045 3.024 3.024 0.282 2044 3.024 3.024 0.282 2043 3.024 3.024 0.282 2042 3.024 3.024 0.282 2041 3.024 3.024 0.282 2040 3.024 3.024 0.282 2039 3.024 3.024 0.282

Step 4 – Determine Activity Hours per Ozone-Season Weekday . The MONTHLY packet within the season.dat file indicates that construction equipment in the Southwest U.S. (“SW”, which includes Texas), are operated 9.1% of their annual total dur ing each summer month. Equivalently, 27.3% (3 summer mo nths x 9.1%/month) of total hou rs per year occur during the summer. This corresponds to 1,306 x 0.273 = 357 hour s of trencher activity per summer. From the Scenario output file we see that a summer NONROAD run is assumed to include 92 days in2-11 the entire season, or 92 / 7 = 13.14 weeks. In turn, this corresponds to 357 hrs/season / 13.14 weeks/season = 27.17 hours per week.

Finally, the DAILY packet of the season.dat file shows that construction equipment is assumed to have 16.7% of its weekly activity occur on a weekday. This corresponds to 27.17 hrs/week x 0.167 = 4.53 hours/summer weekday . This daily activity level can be multiplied using the following equation to estimate tons of NOx per ozone season day, with the summation occurring over engine model years.

Tons/Ozone-Season Weekday = ∑ Emission Factor (g/hp- hr) x Engine Population x Hours/Ozone Season Weekday x Average hp x Load Factor x 1.1023 x 10 - 6 short tons/gram

The resulting emissions estimates are provided in Table F-9 below. These estimates correspond to the values output from the NONROAD model before TexN adjustments are applied.

Table C-9. NOx Emissions from Diesel Trenchers (Tons per Ozone-Season Weekday, 2050 Scenario)

Equipment Age (Yrs) < 50 hp 50 - 75 hp 75-100 hp 1 0.227 0.050 0.008 2 0.201 0.046 0.008 3 0.161 0.043 0.007 4 0.043 0.040 0.007 5 0.020 0.035 0.006 6 0.006 0.026 0.004 7 0.000 0.010 0.002 8 0.000 0.007 0.001 9 0.000 0.004 0.001 10 0.000 0.003 0.000 11 0.000 0.001 0.000 12 0.000 0.000 0.000 Total 0.658 0.266 0.044

Step 5 – Apply Post-Processing Adjustments . Several adjustments ar e applied to the NONROAD outputs. First, temperature and humidity adjust ments are applied to all diesel engines, as discussed in Section 4.3.2. Adju stments utilize absolute humidity (H), which is calculated as follows:

H = [RH x 38.017 x ea] / [P – 6.112 x e a ] where a = [9.8245 x (T – 32)] / [0.556 x (T – 32) + 243.5]

Inserting the parameters specific to typical me teorological year conditions in Harris County identified under Step 1, a = 1.781 and H = 17.330.2-12 There are two adjustment equations – one equati on is used for naturally-aspirated engines, another for turbocharged engines.

Naturally-Aspirated (N-A) Engine Adjustment:

1 + 0.001368 x (0.556 x (T - 32) – 29.444) – 0.01512 x (H – 10.71)

Turbo-charged Engine Adjustment:

1 + 0.00446 x (0.556 x (T – 32) - 25) – 0.018708 x (H – 10.71)

Inserting the values for T ( 81.1) and H from above, the N-A adjustment = 0.897 , and the turbo adjustment = 0.886

.

Next the estimated fraction of N-A and turbocha rged engines (presented in Section 4.3.2) is shown below for model years beyond 2005.

N-A Turbo < 50 hp 0.82 0.18 > 50 hp 0.45 0.55

Applying these weights to the engine adju stments results in a net adjustment of 0.895 for engines less than 50 hp, and 0.891 for engi nes greater than or equal to 50 hp . Applying these factors directly to th e NONROAD output emissions estima tes we obtain the following adjusted NOx values.

< 50 hp 0.5889 TPD 50 – 75 hp 0.2370 TPD 75 – 100 hp 0.0391 TPD Total 0.8650 TPD

Next altitude adjustments are applied directly to NOx emission estimates to reflect the slight increase in hp-hrs needed to accomplish a ta sk at a higher altitude (see Section 4.3.2). Multiplying the 0.865 figure by the altitude adjustme nt factor for Harris County (1.00032) yields a miniscule adjustment of .0003 TPD (0.8653).

The soil adjustment factor for Harris County of 1.222 is applied to all trencher activity, resulting in a one-to-one increase in hp-hrs and NOx emissi ons. The resulting adjustment applied to the 0.8653 figure results in a revise d NOx estimate of 1.0578 TPD.

Finally, Harris County is within the TxLED region, so a further ad justment of (1-.062) = 0.938 is applied to the 1.0578 value, yielding a fi nal adjusted emission estimate of 0.992 TPD for all trenchers operating in Harris County in 2050 . The difference from the actual TexN output of 0.991 TPD is attributable to rounding error.2-13 

## Attachment D

Applicable Rules and Rate of Further Progress (RFP) Analyses2-14 

### Rate of Further Prog ress (RFP) Analyses

TexN can be used to evaluate the effects of individual federal rules impacting non-road emissions for RFP analyses. The applicable rules are:

 Rule #1: Emission Standards for New Nonroad Spark-ignition Engines at or below 19 Kilowatts - “Phase I Small SI Rule” [27]

 Rule #2: Federal Emission Standards for Heavy-Duty and Nonroad Engines - “1998 HD and Nonroad Rule” [28]

 Rule #3: Tier 1, 2 and Tier 3 Emission Standards: Control of Emissions of Air Pollution from Nonroad Diesel Engines - “Tier 1, 2 and 3 Rule” [29]

 Rule #4: Final Phase II Standards fo r Small Nonroad SI Handheld Engines - “Phase II Small SI Rule” [30]

 Rule #5: Emission Standards for New Nonroad Engines: Large Industrial SI Engines, Recreational Vehicles, and Di esel Recreational Marine Engines - “Large SI Rule” [31]

 Rule #6: Clean Air Nonroad Diesel - Ti er 4 Final Rule – “Tier 4 Rule” [32]

In an RFP evaluation, the ozone season-da ily emission reduction impact must be determined and report of each rule for the give n region and evaluation ye ar. Table 6-1 below shows the phase-in dates, equipment types and hp ranges for each rule. Each of these rules is discussed in more detail below.

In order to evaluate individua l rule impacts, the technology t ype files were modified to reflect phase-in of individual rules. There is a separate set of technology type files for each federal rule that is evaluate d. Each rule has a technology type file that reflects the “uncontrolled” conditions and the “controlled” conditions. To create the “uncontrolled” technology type files, the technology type phase-in that was available immediately prior to the rule of evaluation was carried forward to future years, effectively zeroing out the effects of the rule of evaluation. The “controlled” technology t ype files were created by carrying forward the phase-in that was available at the conclusion of the phase-in of the rule of evaluation, effectively zeroing out the effect of subsequent rules.

Note: In some cases, a technology would begin phase-in one year prior to the rule requirements. In these instances, this phase-in year is considered to be a direct consequence of the pending rule. Therefore, any benefits seen by an early phase-in is at tributed to the pending rule.2-15Table D-1. Phase-in Dates by RuleSpark Ignition (Gasoline, LPG, CNG)Compression Ignition (Diesel)RuleReference # RuleSub-categories< 25 hp > 25 hpMARINE< 25 hpMARINE> 25 hp< 50 hp > 50 hpMARINE< 50 hpMARINE> 50 hp1Phase ISmall SI1997-21998 HDandNonroad1998-2006 1998-2000Tier 11999-2000Tier 22001-2006 2001-2006 2001-20063Tier 1,Tier 2andTier 3Tier 32006-2008 2006-20084Phase IISmall SI2002-2007Large IndustrialSpark-IgnitionEngines(Tier 1)20042004Large IndustrialSpark-IgnitionEngines(Tier 2)2007 2007RecreationalVehicles20065 Large SIDieselRecreationalMarine Engines20066 Tier 42008 2008-201316 Rule #1: Emission Standards for New Non-road Spark-ignition (SI) Engines At or Below 19 kW (~25 hp)

This rule is applicable to new non-road SI engines at or below 19 kW (~ 25 hp) and manufactured during or after the 1997 model year, in cluding farm and construction equipment, lawnmowers, string trimmers, edge rs, chainsaws, commercial turf equipment, small construction equipment, and lawn and garden tractors. Exempt vehicles and equipment include competition or combat ve hicles, research, training, investigations, demonstrations, and national security vehicles and equipment, engines used to propel marine vessels, engines used in underground mining equip, motorcycles, aircraft, and recreational vehicles. The st andards for this rule are presented in Table 6-2 below.

Table D-2. Phase I Small SI Rule Standards (g/bhp-hr)

Class Year CO HC HC + NOx NOx Class Description I 1997+ 387 N/A 12 N/A Nonhandheld < 225 cc II 1997+ 387 N/A 10 N/A Nonhandheld > ~225 cc III 1997+ 600 220 N/A 4 Handheld < 20 cc IV 1997+ 600 180 N/A 4 Handheld > ~20 < 50 cc V 1997+ 450 120 N/A 4 Handheld > ~50 cc

Rule #2: Federal Emission Standards for Heavy-Duty and Non-road Engines

This rule is applicable to non-road compression ignition (C I – diesel) engines greater than 50 hp, and marine SI outboard ma nufactured as early as 1998, and personal watercraft and jet boat engines manufactured as early as 1999. This rule does not include standards for non-road SI engines greater than 25 hp or marine CI engines. The standards are presented below in Tables 6-3 and 6-4.

Table D-3. 1998 Non-road CI Engine Standards in g/bhp-hr

Rated Power Year CO HC NOx PM 10 Smoke (%) acceleration/lug /peak modes 50 ≤ hp< 100 1998+ N/A N/A 6.9 N/A 20/15/50 100 ≤ hp< 175 1997+ N/A N/A 6.9 N/A 20/15/50 175 ≤ hp< 750 1996+ 8.5 1 6.9 0.4 20/15/50 hp = 750+ 2000+ 8.5 1 6.9 0.4 20/15/5017 Table D-4. 1998 Marine SI Engine Standards

HC+NOx P* < 4.3 P* ≥ 4.3 Year g/kW-hr g/hphr g/kW-hr g/hp-hr
1998 278 207.3 (0.917 x (151+ 557/P^0.9)) + 2.44 [ (0.917 x (151+ 557/P^0.9)) + 2.44 ] x 0.7457 1999 253 188.7 (0.833 x (151+ 557/P^0.9)) + 2.89 [ (0.833 x (151+ 557/P^0.9)) + 2.89 ] x 0.7457 2000 208 155.1 (0.750 x (151+ 557/P^0.9)) + 3.33 [ (0.750 x (151+ 557/P^0.9)) + 3.33 ] x 0.7457 2001 204 152.1 (0.667 x (151+ 557/P^0.9)) + 3.78 [ (0.667 x (151+ 557/P^0.9)) + 3.78 ] x 0.7457 2002 179 133.5 (0.583 x (151+ 557/P^0.9)) + 4.22 [ (0.583 x (151+ 557/P^0.9)) + 4.22 ] x 0.7457 2003 155 115.6 (0.500 x (151+ 557/P^0.9)) + 4.67 [ (0.500 x (151+ 557/P^0.9)) + 4.67 ] x 0.7457 2004 130 96.9 (0.417 x (151+ 557/P^0.9)) + 5.11 [ (0.417 x (151+ 557/P^0.9)) + 5.11 ] x 0.7457 2005 105 78.3 (0.333 x (151+ 557/P^0.9)) + 5.56 [ (0.333 x (151+ 557/P^0.9)) + 5.56 ] x 0.7457 2006+ 81 60.4 (0.250 x (151+ 557/P^0.9)) + 6.00 [ (0.250 x (151+ 557/P^0.9)) + 6.00 ] x 0.7457 *P = power rating in kilowatts

Rule #3: Tier 1, 2 and 3 Diesel Engine Emission Standards

These emission standards apply to all non-road mobile diesel engines and equipment of all sizes, except for locomotiv es, marine engines above 50 hp, underground mining equipment, and engines with less than 50 cc that are typically used in model airplanes. The standards are presented in Table 6-5 below.

Table D-5. Tier 1, 2 and 3 Diesel Engine Standards in g/kW-hr (g/hp-hr)

Engine Size Tier Model year NMHC + NOx CO PM 10 Tier 1 2000 10.5 (7.8) 8.0 (6.0) 1.0 (0.75) kW < 8 (hp < 11) Tier 2 2005 7.5 (5.6) 8.0 (6.0) 0.8 (0.6) Tier 1 2000 9.5 (7.1) 6.6 (4.9) 0.8 (0.6) 8 ≤ kW < 19 (11 ≤ hp< 25) Tier 2 2005 7.5 (5.6) 6.6 (4.9) 0.8 (0.6) Tier 1 1999 9.5 (7.1) 5.5 (4.1) 0.8 (0.6) 19 ≤ kW< 37 (25 ≤ hp< 50) Tier 2 2004 7.5 (5.6) 5.5 (4.1) 0.6 (0.45) Tier 2 2004 7.5 (5.6) 5.0 (3.7) 37 ≤ kW< 75 (50 ≤ hp< 100) Tier 3 2008 4.7 (3.5) 5.0 (3.7) 0.4 (0.3)
Tier 2 2003 6.6 (4.9) 5.0 (3.7) 75 ≤ kW< 130 (100 ≤ hp< 175) Tier 3 2007 4 (3.0) 5.0 (3.7) 0.3 (0.22)
Tier 2 2003 6.6 (4.9) 3.5 (2.6) 130 ≤ kW< 225 (175 ≤ hp< 300) Tier 3 2006 4 (3.0) 3.5 (2.6) 0.2 (0.15)
Tier 2 2001 6.4 (4.8) 3.5 (2.6) 225 ≤ kW < 450 (300 ≤ hp < 600) Tier 3 2006 4 (3.0) 3.5 (2.6) 0.2 (0.15)
Tier 2 2002 6.4 (4.8) 3.5 (2.6) 450 ≤ kW < 560 (600 ≤ hp< 750) Tier 3 2006 4 (3.0) 3.5 (2.6) 0.2 (0.15)

kW ≥ 560 (hp ≥ 750) Tier 2 2006 6.4 (4.8) 3.5 (2.6) 0.2 (0.15)

Rule #4: Phase II Standards for Small Non-road SI Handheld Engines18 The Phase II Standards for small handheld non-road spark-ignition engines apply to the following classes of engines shown in Table 6-6. Phase II standards are presented in Table 6-7.

Table D-6. Phase II Small Non-road SI Engine Categories

Class Type cc* I-A Nonhandheld cc < 66 I-B Nonhandheld 66 to 100 cc I Nonhandheld 100 to 225 c II Nonhandheld > ~225 cc III Handheld < 20 cc IV Handheld 20 to 50 cc V Handheld > ~50 cc * displacement in cubic centimeters

Table D-7. Phase II HC+NOx Standards for Handheld Engines in g/kW-hr (g/hphr)

Model Year Class III Class IV Class V 2002 238 (177) 196 (146) N/A 2003 175 (130) 148 (110) N/A 2004 113 (84) 99 (74) 143 (107) 2005 50 (37) 50 (37) 119 (89) 2006 50 (37) 50 (37) 96 (72) 2007+ 50 (37) 50 (37) 72 (54)

Rule #5: Large Industrial SI Engines, Recreational Vehicles, and Diesel Recreational Marine Engines

This rule applies to larg e industrial spark-ignition engines powered by gasoline, natural gas, or propane gas, rated over 19 kW (25 hp). The rule also applies to diesel marine engines over 37 kW (50 hp) used in recreational boats, such as yachts and cruisers. This rule does not apply to spark-ignition recr eational marine vessels. The standards are presented in Tables D-8 through D-11.

Table D-8. Large SI Engine Standards in g/kW-hr (g/hp-hr)

Tier/Year HC+NOx CO Tier I Starting in 2004 4 (3.0) 50 (37.3) Tier 2 Starting in 2007 2.7 (2.0) 4.4 (3.3)19 Table D-9. Recreational Vehicles Standards in g/kW-hr (g/hp-hr)

Vehicle Model Year HC CO Phase-in % 2006 100 (74.6) 275 (205.1) 50 2007 - 2009 100 (74.6) 275 (205.1) 2010 75 (55.9) 275 (205.1) Snowmobiles
2012 75 (55.9) 200 (149.1) 100

2006 2 (1.5) 25 (18.6) 50 Off-highway Motorcycles 2007+ 2 (1.5) 25 (18.6) 100 2006 1.5 (1.1) 35 (26.1) 50 ATVs 2007+ 1.5 (1.1) 35 (26.1) 100

Table D-10. Permeation Standards for Recreational Vehicles

Emission Component Implementation Date Standard Test Temperature Fuel Tank Permeation 2008 1.5 g/sq meters/day 28 Degrees C (82 degrees F) Fuel Hose Permeation 2008 15 g/sq meters/day 23 Degrees C (73 degrees F)

Table D-11. Recreational Diesel Marine Standards in g/kW-hr (g/hp-hr)

Engine size Implementation Date HC + NOx PM 10 CO 0.5 L/cyl ≤ Displacement< 0.9 L/cyl 2007 7.5 (5.59) 0.4 (0.30) 5 (3.73) 0.9 L/cyl ≤ Displacement< 1.2 L/cyl 2006 7.2 (5.37) 0.3 (0.22) 5 (3.73) 1.2 L/cyl ≤ Displacement< 2.5 L/cyl 2006 7.2 (5.37) 0.2 (0.15) 5 (3.73) Displacement ≥ 2.5 L/cyl 2009 7.2 (5.37) 0.2 (0.15) 5 (3.73)

Rule #6: Tier 4 Diesel Rule

This rule introduces new emission standards for non-road diesel engines and sulfur reductions for non-road diesel fuel. This rule will reduce PM emissions by 95% and NOx emissions by 90% and virtually eliminate sulfur oxides. The sulfur level in non-road diesel fuel will be reduced from 3,000 ppm to 500 ppm starting in 2007, and then to 15 ppm starting in 2010. The sulfur reductions make it possible for manufacturers to use clean engine technologies to reduce pollution, similar to thos e being introduced in on-road vehicles. These new engine sta ndards will take effect, based on engine hp, beginning in 2008. This rule applies to diesel engines used primarily in most construction, agricultural, indus trial, and airport support equipment. The standards will be fully phased in by 2014, though engines grea ter than 750 hp will have an additional year (2015) to comply. The Tier 4 st andards are presented in Table D-12.20 Table D-12. Tier 4 Emissions Standards (g/bhp-hr)

Rated Power First year the standards apply PM 10 NOx hp < 25 2008 0.3

- 25 ≤ hp < 75 2013 0.02 3.5 75 ≤ hp < 175 2012 - 2013 0.01 0.3 175 ≤ hp <750 2011 - 2013 0.01 0.3

2011 - 2014 0.075 0.5 (gensets greater than 1,200 hp); 2.6 (all other) hp ≥ 750 2015 0.02 (gensets); 0.03 (all other engines) 0.5 (gensets only)

To use TexN to evaluate the effects of i ndividual federal rules, after selecting the region and analysis year of interest go to the Period and Controls tab (as seen in Figure D-2) of the application and select the rule you are inte rested in evaluating.

Figure D-2. Period and Controls Tab

When the scenario is executed, NONROA D must be executed twice by the user for each rule evaluation. The first run w ill use technology type files reflecting the controls up to, but not including the rule of interest. Thes e are the “uncontrolled”, or baseline, runs. The second run will use technology type files reflecting the controls21 enacted by the rule of interest, but does not include any rules subse quent to the rule of interest. These are the “contro lled” runs. The rule impact s are calculated by subtracting the controlled run emissions from the uncontrolled run emissions for each rule, and then summing the differences across all rules for each SCC.22 

## Federal Non-Road Rule / SCC Crosswalk

Rule #1 226X002XXX ( hp < 25 ) 226X003XXX ( hp < 25 ) 226X004XXX ( hp < 25 ) 226X005XXX ( hp < 25 ) 226X006XXX ( hp < 25 ) 226X007XXX ( hp < 25 ) 226X008XXX ( hp < 25 )

226X010010 ( hp < 25 ) 2285004XXX ( hp < 25 ) 2285006XXX ( hp < 25 ) Rule #2 227XXXXXXX (hp > 50 ) 2285002XXX ( hp > 50 ) 22820050XX ( hp < 25 ) 2282010005 ( hp < 25 ) Rule #3 2270001XXX 2270002XXX 2270003XXX 2270004XXX 2270005XXX 2270006XXX 2270007XXX 2270008XXX

2270010010 22820200XX (hp < 50 ) Rule #4 226XXXXXXX ( hp < 25 )

2285004XXX ( hp < 25 ) Rule # 5 226XXXXXXX ( hp > 25 )

22820050XX ( hp > 25 ) 2282010005 ( hp > 25 ) 2285004XXX ( hp > 25 ) 2285006XXX ( hp > 25 ) 22820200XX ( hp > 50 ) Rule #6 227XXXXXXX

2285002XXX 22820200XX23